From be8520272de4b422d1a3b0e31b43ddbc241af004 Mon Sep 17 00:00:00 2001 From: Rodolphe Griset <114246360+Griset@users.noreply.github.com> Date: Fri, 8 Nov 2024 10:05:16 +0100 Subject: [PATCH] Upload library --- CMakeLists.txt | 99 + Graph.cpp | 170 + Graph.h | 140 + LICENSE | 2 +- README.md | 140 +- cmake/FindCPLEX.cmake | 44 + cmake/FindNLopt.cmake | 38 + coloring/Branching.cpp | 98 + coloring/Branching.h | 36 + coloring/ConstraintHandler.cpp | 133 + coloring/ConstraintHandler.h | 127 + coloring/Pricer.cpp | 129 + coloring/Pricer.h | 114 + coloring/Probdata.cpp | 171 + coloring/Probdata.h | 103 + coloring/Vardata.cpp | 5 + coloring/Vardata.h | 36 + coloring/coloring.cpp | 94 + coloring/coloring.h | 22 + main.cpp | 88 + mwis/LocalSearch.cpp | 108 + mwis/LocalSearch.h | 61 + mwis/cplex.cpp | 70 + mwis/greedy.cpp | 101 + mwis/mwis.h | 65 + nlopt-2.7.1.tar.gz | Bin 0 -> 2044180 bytes quantum/Hamiltonian.cpp | 396 + quantum/Hamiltonian.h | 160 + test_data/graphs_100/Complete.mwis | 5052 ++ test_data/graphs_100/Empty.mwis | 102 + test_data/graphs_100/GNP_0.1.mwis | 617 + test_data/graphs_100/GNP_0.3.mwis | 1657 + test_data/graphs_100/GNP_0.5.mwis | 2565 + test_data/graphs_100/Star.mwis | 203 + test_data/graphs_100/Tree.mwis | 201 + test_data/graphs_20/Complete.mwis | 212 + test_data/graphs_20/Empty.mwis | 22 + test_data/graphs_20/GNP_0.1.mwis | 41 + test_data/graphs_20/GNP_0.3.mwis | 85 + test_data/graphs_20/GNP_0.5.mwis | 118 + test_data/graphs_20/Star.mwis | 43 + test_data/graphs_20/Tree.mwis | 41 + test_data/graphs_40/GNP_0.1.mwis | 122 + test_data/graphs_40/GNP_0.2.mwis | 213 + test_data/graphs_40/GNP_0.3.mwis | 222 + test_data/graphs_40/GNP_0.4.mwis | 346 + test_data/graphs_40/GNP_0.5.mwis | 432 + test_data/graphs_40/GNP_0.6.mwis | 510 + test_data/graphs_40/GNP_0.7.mwis | 594 + test_data/graphs_40/GNP_0.8.mwis | 669 + test_data/graphs_40/GNP_0.9.mwis | 746 + test_data/graphs_400/Complete.mwis | 80202 +++++++++++++++++++ test_data/graphs_400/Empty.mwis | 402 + test_data/graphs_400/GNP_0.1.mwis | 8527 ++ test_data/graphs_400/GNP_0.3.mwis | 24197 ++++++ test_data/graphs_400/GNP_0.5.mwis | 40240 ++++++++++ test_data/graphs_400/RandomRegular_10.mwis | 2401 + test_data/graphs_400/RandomRegular_3.mwis | 1001 + test_data/graphs_400/RandomRegular_5.mwis | 1401 + test_data/graphs_400/Star.mwis | 803 + test_data/graphs_400/Tree.mwis | 801 + 61 files changed, 177487 insertions(+), 51 deletions(-) create mode 100644 CMakeLists.txt create mode 100644 Graph.cpp create mode 100644 Graph.h create mode 100644 cmake/FindCPLEX.cmake create mode 100644 cmake/FindNLopt.cmake create mode 100644 coloring/Branching.cpp create mode 100644 coloring/Branching.h create mode 100644 coloring/ConstraintHandler.cpp create mode 100644 coloring/ConstraintHandler.h create mode 100644 coloring/Pricer.cpp create mode 100644 coloring/Pricer.h create mode 100644 coloring/Probdata.cpp create mode 100644 coloring/Probdata.h create mode 100644 coloring/Vardata.cpp create mode 100644 coloring/Vardata.h create mode 100644 coloring/coloring.cpp create mode 100644 coloring/coloring.h create mode 100644 main.cpp create mode 100644 mwis/LocalSearch.cpp create mode 100644 mwis/LocalSearch.h create mode 100644 mwis/cplex.cpp create mode 100644 mwis/greedy.cpp create mode 100644 mwis/mwis.h create mode 100644 nlopt-2.7.1.tar.gz create mode 100644 quantum/Hamiltonian.cpp create mode 100644 quantum/Hamiltonian.h create mode 100644 test_data/graphs_100/Complete.mwis create mode 100644 test_data/graphs_100/Empty.mwis create mode 100644 test_data/graphs_100/GNP_0.1.mwis create mode 100644 test_data/graphs_100/GNP_0.3.mwis create mode 100644 test_data/graphs_100/GNP_0.5.mwis create mode 100644 test_data/graphs_100/Star.mwis create mode 100644 test_data/graphs_100/Tree.mwis create mode 100644 test_data/graphs_20/Complete.mwis create mode 100644 test_data/graphs_20/Empty.mwis create mode 100644 test_data/graphs_20/GNP_0.1.mwis create mode 100644 test_data/graphs_20/GNP_0.3.mwis create mode 100644 test_data/graphs_20/GNP_0.5.mwis create mode 100644 test_data/graphs_20/Star.mwis create mode 100644 test_data/graphs_20/Tree.mwis create mode 100644 test_data/graphs_40/GNP_0.1.mwis create mode 100644 test_data/graphs_40/GNP_0.2.mwis create mode 100644 test_data/graphs_40/GNP_0.3.mwis create mode 100644 test_data/graphs_40/GNP_0.4.mwis create mode 100644 test_data/graphs_40/GNP_0.5.mwis create mode 100644 test_data/graphs_40/GNP_0.6.mwis create mode 100644 test_data/graphs_40/GNP_0.7.mwis create mode 100644 test_data/graphs_40/GNP_0.8.mwis create mode 100644 test_data/graphs_40/GNP_0.9.mwis create mode 100644 test_data/graphs_400/Complete.mwis create mode 100644 test_data/graphs_400/Empty.mwis create mode 100644 test_data/graphs_400/GNP_0.1.mwis create mode 100644 test_data/graphs_400/GNP_0.3.mwis create mode 100644 test_data/graphs_400/GNP_0.5.mwis create mode 100644 test_data/graphs_400/RandomRegular_10.mwis create mode 100644 test_data/graphs_400/RandomRegular_3.mwis create mode 100644 test_data/graphs_400/RandomRegular_5.mwis create mode 100644 test_data/graphs_400/Star.mwis create mode 100644 test_data/graphs_400/Tree.mwis diff --git a/CMakeLists.txt b/CMakeLists.txt new file mode 100644 index 0000000..4753e66 --- /dev/null +++ b/CMakeLists.txt @@ -0,0 +1,99 @@ +cmake_minimum_required(VERSION 3.13.4) +project(Quantum_BnP) + +set(CMAKE_MODULE_PATH "${PROJECT_SOURCE_DIR}/cmake" ${CMAKE_MODULE_PATH}) +set(CMAKE_CXX_STANDARD 20) +set(CMAKE_CXX_FLAGS "-DIL_STD") +SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pthread") + +################################################################################################################################### +###################################################### Path Library settings ###################################################### +################################################################################################################################### + +set(NLopt_INSTALL_DIR "${PROJECT_SOURCE_DIR}/nlopt_install") +option(QB_ENABLE_SCIP "Use of SCIP library" OFF) +set(SCIP_DIR YOU_PATH_TO_SCIP) + + +option(QP_ENABLE_CPLEX "Use of CPLEX solver" OFF) +set(ENV{CPLEX_ROOT} YOU_PATH_TO_CPLEX) + + +############################################################################################################ +############################################################################################################ +set(CMAKE_MODULE_PATH "${PROJECT_SOURCE_DIR}/cmake" ${CMAKE_MODULE_PATH}) + + +if (QB_ENABLE_SCIP) + find_package(SCIP REQUIRED) +endif() + +if(QP_ENABLE_CPLEX) + + add_library(CPLEX INTERFACE IMPORTED) + FIND_PACKAGE(CPLEX REQUIRED) + set(ADDITIONAL_LIBRARIES + ${CPLEX_LIBRARY} + ${CPLEX_LIBRARY_CONCERT}) + + link_directories(${CPLEX_INCLUDE_DIRS}) + link_directories(${CPLEX_LIBRARIES}) +endif() + + + + + + +list(APPEND COLORING coloring/Branching.cpp coloring/Branching.h coloring/coloring.cpp coloring/coloring.h coloring/ConstraintHandler.cpp coloring/ConstraintHandler.h coloring/Pricer.cpp coloring/Pricer.h coloring/Probdata.cpp coloring/Probdata.h coloring/Vardata.cpp coloring/Vardata.h) +list(APPEND MWIS mwis/greedy.cpp mwis/LocalSearch.cpp mwis/LocalSearch.h mwis/mwis.h mwis/cplex.cpp) +list(APPEND BASICS Graph.h Graph.cpp) +list(APPEND QUANTUM quantum/Hamiltonian.h quantum/Hamiltonian.cpp) +file(GLOB SOURCE coloring/*) + + + +find_package(OpenMP) +find_library(OPENBLAS openblas) +find_package(NLopt REQUIRED) + +set(PROJECT_INCLUDE_DIRS + ${CMAKE_CURRENT_SOURCE_DIR}/mwis + ${CMAKE_CURRENT_SOURCE_DIR}/coloring + ${CMAKE_CURRENT_SOURCE_DIR}/quantum + ${CPLEX_INCLUDE_DIR} + ${CPLEX_INCLUDE_DIR}/ilcplex + ${CONCERT_INCLUDE_DIR} + ${CONCERT_INCLUDE_DIR}/ilconcert + ${NLOPT_INCLUDE_DIRS}) + +foreach(include_dir ${PROJECT_INCLUDE_DIRS}) + include_directories(${include_dir}) + file(GLOB tmp_headers + ${include_dir}/*.hpp + ${include_dir}/*.hx + ${include_dir}/*.h) + list(APPEND header_files ${tmp_headers}) +endforeach() + + +link_directories(${NLOPT_LIBRARY_DIRS}) +link_directories(${NLopt_INSTALL_DIR}/lib) + + +add_executable(Quantum_BnP main.cpp ${BASICS} ${MWIS} ${QUANTUM} ${COLORING} ${CPLEX_INCLUDE_DIRS} ${ADDITIONAL_LIBRARIES} ) +target_compile_definitions(Quantum_BnP INTERFACE -DIL_STD) +target_link_libraries(Quantum_BnP PUBLIC ${CMAKE_DL_LIBS} ${ADDITIONAL_LIBRARIES}) + +target_link_libraries(Quantum_BnP PUBLIC nlopt) + + +if(QP_ENABLE_CPLEX) + target_link_libraries(Quantum_BnP INTERFACE ${CPLEX_LIBRARIES} pthread) + target_include_directories(Quantum_BnP INTERFACE ${CPLEX_INCLUDE_DIRS}) + target_link_libraries(Quantum_BnP PUBLIC ${CPLEX_LIBRARIES}) +endif() + +if(QP_ENABLE_SCP) + target_link_libraries(Quantum_BnP PUBLIC ${SCIP_LIBRARIES}) +endif() diff --git a/Graph.cpp b/Graph.cpp new file mode 100644 index 0000000..3a6ff58 --- /dev/null +++ b/Graph.cpp @@ -0,0 +1,170 @@ +// +// Created by margarita on 11/10/22. +// + +#include +#include +#include "Graph.h" +#include + +#define LINE_SIZE 255 + +void Graph::init_empty(const int &size) { + weights.resize(size, 0); + node_number = size; + for(int i = 0; i < size; i++) { + representors[i] = i; + active_nodes.insert(i); + } +} + +WTYPE Graph::get_max_weight() const { + if(! weighted) + return 1; + + auto it = active_nodes.begin(); + WTYPE max_weight = abs(weights.at(*it)); + it++; + + while (it != active_nodes.end()) { + max_weight = max(max_weight, abs(weights.at(*it))); + it++; + } + return max_weight; +} + +void Graph::add_node_weight(const N_ID& u, const WTYPE& weight){ + N_ID u_rep = representors[u]; + weights[u_rep] += weight; +}; + + +void Graph::add_edge(const N_ID& u, const N_ID& v) { + if (!active_nodes.count(u) || !active_nodes.count(v)) + throw invalid_argument("One of the nodes isn't active"); + else if (u != v) { + adj_list[u].insert(v); + adj_list[v].insert(u); + } +}; +bool Graph::has_edge(const N_ID &u, const N_ID& v) const { + if (!active_nodes.count(u) || !active_nodes.count(v)) + throw invalid_argument("One of the nodes isn't active"); + if (adj_list.find(u)==adj_list.end()) + return false; + else return adj_list.at(u).count(v); +}; + +void Graph::merge_nodes(const N_ID &u, const N_ID& v) { + N_ID rep_u = representors.at(u); + N_ID rep_v = representors.at(v); + + if(has_edge(rep_u, rep_v)) + throw "Connected nodes can't be merged"; + + active_nodes.erase(rep_v); + for( auto& p: representors ) + if (p.second == rep_v) + p.second = rep_u; + + adj_list[rep_u].insert(adj_list[rep_v].begin(), adj_list[rep_v].end()); + + //Modify the adjacency list of rep_v's neighbors + for(const auto& v_neighbor : adj_list[rep_v]){ + adj_list[v_neighbor].insert(rep_u); + adj_list[v_neighbor].erase(rep_v); + } + + adj_list.erase(rep_v); + return; +}; + +void Graph::split_nodes(const N_ID &u, const N_ID& v){ + N_ID rep_u = representors.at(u); + N_ID rep_v = representors.at(v); + + add_edge(rep_u, rep_v); + return; +}; + +N_CONTAINER Graph::recover_all_merged_to(const N_CONTAINER &set) { + N_CONTAINER result = set; + for(int i = 0; i < node_number; i++){ + if (set.count(representors[i])) + result.insert(i); + } + return result; +} + +void Graph::init_node_weights(const vector& new_weights) { + if (new_weights.size() != node_number) + throw invalid_argument("The size of the vector with weights doesn't match the number of nodes"); + for(auto i: active_nodes) + set_node_weight(i, new_weights[i]); + for(int i = 0; i < node_number; i++) + if(!active_nodes.count(i)) + add_node_weight(i, new_weights[i]); +}; + +void Graph::read_dimacs(const string& filename) { + ifstream file; + file.open(filename); + + char c, comment[LINE_SIZE]; + N_ID u, v; + WTYPE weight; + int n_nodes, n_edges; + weighted = false; + + while (file) + { + file >> c; + switch (c) { + case 'c': + file.getline(comment, LINE_SIZE); + break; + case 'p': { + file >> comment >> n_nodes >> n_edges; + init_empty(n_nodes); + edge_number = n_edges; + break; + } + case 'e': { + file >> u >> v ; + if (n_edges >= 0) { + add_edge(u-1, v-1); + n_edges--; + } else { + file.close(); + cerr << "No more edges to add.\n"; + } + break; + } + case 'n': { + weighted = true; + file >> u >> weight ; + set_node_weight(u-1, weight); + break; + } + default : + { + cerr << "Unknown command. Reading aborted." << std::endl; + file.close(); + break; + } + } + } + if(!weighted){ + for(int u = 0; u < n_nodes; u++) + weights[u] = 1; + } + file.close(); +}; + +bool is_independent_set(const Graph& G, const N_CONTAINER& IS){ + for(const auto & u: IS) + for( const auto & v: IS) + if (u!=v & G.has_edge(u, v)) + return false; + return true; +} \ No newline at end of file diff --git a/Graph.h b/Graph.h new file mode 100644 index 0000000..cff69ce --- /dev/null +++ b/Graph.h @@ -0,0 +1,140 @@ +// +// Created by margarita on 11/10/22. +// + +#ifndef QUANTUM_BNP_GRAPH_H +#define QUANTUM_BNP_GRAPH_H + +#include +#include +#include +#include + +using namespace std; + +//Type of the unique node identifier +using N_ID = int; + +//Type of node weights +using WTYPE = double; + +//The largest value of weight +#define INF numeric_limits::max() + +//If a WTYPE variable has a value lower than EPSILON we assume it to be zero +#define EPSILON 10*numeric_limits::epsilon() + +//Type of node lists +using N_CONTAINER = set; + +//Graph without loops +class Graph { +private: + bool weighted; + int node_number; + + int edge_number; + vector weights; //TODO I chainged the type, see what crushes + unordered_map adj_list; + + // The indexes of nodes that were not merged to others + N_CONTAINER active_nodes; + + // If representator[u] != u than the node u was merged to representator[u] + unordered_map representors; + + /** Create an empty graph + * + * @param size number of nodes + * @note nodes are indexed from 0 to size, each node is its own representor + */ + void init_empty(const int& size); +public: + bool is_weighted() const { return weighted; }; + int get_node_number() const { return node_number; }; + int get_edge_number() const { return edge_number; }; + int get_degree(const N_ID& u) const { if (!active_nodes.count(u)) throw invalid_argument("The node isn't active"); else return adj_list.at(u).size(); }; + N_CONTAINER get_neighbors(const N_ID& u) const { const std::set emptyReturn; return (adj_list.find(u) != adj_list.end()) ? adj_list.at(u) : emptyReturn;} + N_CONTAINER get_active_nodes() const { return active_nodes; }; + + WTYPE get_node_weight(const N_ID& u) const { if (!active_nodes.count(u)) throw invalid_argument("The node isn't active"); else return weights.at(u); } ; + WTYPE get_nodeset_weight(const N_CONTAINER& set) const { WTYPE res = 0; for(const auto& u: set) res += get_node_weight(u); return res; } + + /**Computes the largest absolute weight of an active node in the graph + * + * @return + */ + WTYPE get_max_weight() const; + /** Return the difference between the node weight and the cumulate weight of its neighbors + * + * @param u + * @return + */ + WTYPE get_surplus(const N_ID& u) const { auto w = get_node_weight(u); for(const auto & v: adj_list.at(u)) w -= get_node_weight(v); return w; }; + + void set_weights_to_zero() {fill(weights.begin(), weights.end(), 0); } + + /** Set the new weight to an active node + * + * @param u + * @param weight + * @throw invalid_argument if the node u isn't active + */ + void set_node_weight(const N_ID& u, const WTYPE& weight) { if (!active_nodes.count(u)) throw invalid_argument("The node isn't active"); else weights[u] = weight; }; + + /** Add the weight of an inactive node to the weight of its representor + * + * @param u + * @param weight + * @note used in the pricing procedure + */ + void add_node_weight(const N_ID& u, const WTYPE& weight); + + void add_edge(const N_ID& u, const N_ID& v); + bool has_edge(const N_ID &u, const N_ID& v) const; + + /** Merge the nodes u and v + * + * u and v get the same representor. The method merges all nodes previously merged to v (v included) to the representor of u. + * The number of active nodes decreases + * + * @param u + * @param v + * @return + * @throw TODO an exception when nodes rep_u and rep_v are connected + */ + void merge_nodes(const N_ID &u, const N_ID& v); + + /** Add an edge between the representors of u and v + * + * @param u + * @param v + * @return + */ + void split_nodes(const N_ID &u, const N_ID& v); + + /** Initialize the weights of active nodes from a vector + * + * @param new_weights + * @note is used in the Pricing step + */ + void init_node_weights(const vector& new_weights); + + /** Initialize the edge lists end the node weights from a file + * + * @param filename + * @throw TODO (and exception if the filename is invalid or the file doesn't respect the DIMACS format) + */ + void read_dimacs(const string& filename); + + /** Find all nodes that are merged to nodes in the input container + * + * @param set + * @return + */ + N_CONTAINER recover_all_merged_to(const N_CONTAINER& set); +}; + +bool is_independent_set(const Graph& G, const N_CONTAINER& IS); + +#endif //QUANTUM_BNP_GRAPH_H diff --git a/LICENSE b/LICENSE index ec7f718..82ef9a6 100644 --- a/LICENSE +++ b/LICENSE @@ -284,4 +284,4 @@ the rights granted in Article 2 of this Licence and protect the covered Source Code from exclusive appropriation. All other changes or additions to this Appendix require the production of a new -EUPL version. +EUPL version. \ No newline at end of file diff --git a/README.md b/README.md index 7341272..ef07207 100644 --- a/README.md +++ b/README.md @@ -1,74 +1,114 @@ -# NEASQC lib template +# Benchmarking suite for smart charging : NEASQC WP 5.10 -This repository is a template for NEASQC libraries. +This readme correspond to the benchmarking suite for smart charging problems studied in the [NEASQC](https://neasqc.eu/) developped during the PhD work of Margarita Veshchezerova : Quantum algorithms for the [energy management optimization problems](https://theses.hal.science/tel-04105922/) [3]. -## Licence +This library is a software implementing a quantum-inspired approach and compares it to classical approaches. -The `LICENCE` file contains the default licence statement as specified in the proposal and partner agreement. +**This program allows to compute the Maximum Weighted Independed Set in a graph and the Graph Coloring.** -## Building and installing +# Basic Installation procedure +* The library require NLopt (version 2.7.1), a .tar.gz archive of NLopt is inside the library +1) Install Nlopt in nlopt_install folder + 1.1) Uncompress Nlopt library : `tar -xzf nlopt-2.7.1.tar.gz` + 1.2) Move in nlopt-2.7.1 folder : `cd nlopt-2.7.1` + 1.3) Compile nlopt and install it : + `cmake .` + `make -j` + `cmake --install . --prefix ${PATH_TO_CURRENT_FOLDER}/nlopt_install` +2) Library installation + 2.1) Get back in the root folder `cd ..` + 2.2) cmake . + 2.3) make -j -For simplicity, an example of `setup.py` file is provided in this template. -Feel free to modify it if you have exotic build recipes. +The binary file QUANTUM_BNP should be created at the root folder of the library. +## The library implement two heuristics for Maximum Weighted Independent Set : +- Heuristic 1 : greedy initialization from [1] enhanced with a local search [2]. +- Heuristic 2 : firstly optimize the corresponding energy Hamiltonian with the hybrid quantum routine **RQAOA** [4] to further improve the obtained assignment with the local search [2]. -## Coding conventions +Remark : Due to the parameter optimization routine the quantum heurisic is probabilistic, so the result may change between executions. If the quantum heuristic is not working very well, it may be due to the suboptimal values of parameters. In this case modify the macros MAX_OPT_TIME in Hamiltonian.cpp (initially set to 5). -In order to simplify the coding conventions, we provide a pylint.rc file in `misc/pylint.rc`. -This will allow you to easily check your naming conventions and various other aspects. -This is not a strict guidline, as pylint can be quite pedantic sometimes (but also very helpful). +To see the link between smart charging problems and the two problems solved by the library we refer to [3]. -A few remarks: -- pylint can be integrated in most editors (and we strongly advise you to) -- running pylint on several source files in one go can find errors such as circular imports or code duplication: +# Additional library installation +## Optionnaly The library implement two exact methods for Maximum Weighted Independent Set but which might require advance settings : +- Exact 1 : implementation of the SEWELL method introduced in [1]. +- Exact 2 : solves the corresponding Integer Linear Program with CPLEX -```bash -python -m pylint --rcfile=./misc/pylint.rc -``` -or +To activate those liraries you need to activate the corresponding QB_ENABLE_ option of the library and to change the corresponding set environnement line, the corresponding lines are between line 14 and 18 of the CMakeList : + option(QB_ENABLE_SCIP "Use of SCIP library" OFF) + set(SCIP_DIR YOU_PATH_TO_SCIP) + option(QP_ENABLE_CPLEX "Use of CPLEX solver" OFF) + set(ENV{CPLEX_ROOT} YOU_PATH_TO_CPLEX) -```bash -pylint --rcfile=./misc/pylint.rc -``` +## Version +* SCIP (version 8.0.2) +* cplex (version 12.7) -depending on how you installed pylint. -## Testing and continuous integration -In order to uniformise the continuous integration process across libraries, we will assume that: -- all the tests related to your library are compatible with pytest -- there exists a 'test' recipe in the `setup.py` file +## The graph coloring solution is computed with the **Quantum-assisted Branch & Price** [3]. + The Branch & Price procedure is implemented using SCIP library (version 8.0.0). The branching is done with *Ryan-Foster rule*. + The coloring procedure stops either when the optimal coloring is found or after the TIMELIMIT (specified at line 41 of the coloring.cpp file) seconds. -The default test recipe (in this template) simply calls pytest on the full repository. -Pytest detects: -- any file that starts with test\_ (e.g test\_my\_class.py) -- inside these files, any function that starts test\_ -- any class that starts with Test -You can run it with: +# Library test +The program receives in input from 2 to 3 arguments. + *Quantum_BnP -solved_problem -instance_file (optional) -method* -```bash -python setup.py test -``` +* *-solved_problem* indicates if we solve the graph coloring ( *-COLORING* ) or the Maximum Weighted Independent Set problem ( *-MWIS* ) +* *-instace_file* describes the instance in the DIMACS format (node indexes start at 1): + General graph data + * p #nodes #edges + + The list of the edges: + * e u v + * ... + * e u v + + The list of node weights (if not provided every node is assigned the weight 1) + * n 1 weight + * ... + * n n weight + * c ... May be used in any line for comments + * If the line starts with any other character than c, p, e and n the execution is aborted +* *-method*: for the MWIS problem specifies which exact or heuristic method should be called. Possible values are *-CPLEX* and *-sewell* (for exact methods) and *-greedy* or *-quantum* for heuristics -This way, you can write tests either right next to the corresponding code (convenient) or in a `tests` folder at the root of the repository. +The program outputs in the standard output: +* For the MWIS problem - The set that was found by the specified method +* For the graph coloring problem - the color assingment and the RQAOA success rate -If you are not familiar with unit testing and you feel that it's too much for your project, that's fine. -The bare minimum would be to include some run examples wrapped in test functions (functional tests). +# Examples : -Remark that in this template, the same tests are in my\_lib/test\_my\_lib.py and tests/test\_my\_lib.py. +## For the *Maximum Independent Set* problem: "QUANTUM_BNP -MWIS test_data/graphs_100/GNP_0.5.mwis -quantum". +The expected (probabilistic) output is: -## GitHub CI -This repository contains a GitHub Workflow file that will automatically run pytest when changes are pushed. -Details on disabling and enabling this feature can be found [here](https://docs.github.com/en/enterprise-server@3.0/actions/managing-workflow-runs/disabling-and-enabling-a-workflow). +     MWIS is independent: 1 -## Documentation -Customize the GitHub Workflow YAML file: *repo_name*/.github/workflow/sphinx\_doc.yml -There is a basic index.rst template under 'doc'. Modify it as you want. +     -quantum returned an independent set of value: 9 -Any modification under the folder 'doc' pushed to GitHub will trigger a rebuild of the documentation (using GitHub CI). -If the build is successful, then the resulting html documentation can be access at: https://neasqc.github.io/repo_name +     The set is: 13 27 32 34 56 63 88 94 99 -Notes: - - You can follow the build process on the 'Actions' tab below the name of the repository. - - neasqc.github.io does not immediately update. You may need to wait a minute or two before it see the changes. +## For the *Coloring* problem you need to activate SCIP : "QUANTUM_BNP -COLORING test_data/graphs_20/GNP_0.5.mwis". +The expected output is: + +     Branch & Price found a coloring with 6 colors. + +     RQAOA success rate is: 1 + +     COLORING: 0 3 1 5 2 4 3 5 4 5 1 2 5 1 0 2 4 2 0 2 + +The folder test_data contains simple graphs of different node number and density. +Each folder *graphs_n* in test_data contains graphs with *n* nodes. +Files *GNP_0.d.mwis* are randomly generated instances with density *d*. + +# AKNOWLEDGEMENTS AND BIBLIOGRAPHY +This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951821. + +[1] https://www.math.uwaterloo.ca/~bico/papers/safe_color.pdf + +[2] https://www.researchgate.net/publication/221131653_Fast_Local_Search_for_the_Maximum_Independent_Set_Problem + +[3] Veshchezerova, M. (2022). Quantum algorithms for energy management optimization problems. Theses, UniversitĂ© de Lorraine, December. + +[4] Bravyi et al., 2020 Sergey Bravyi, Alexander Kliesch, Robert Koenig, and Eugene Tang. Obstacles to variational quantum optimization from symmetry protection. Phys. Rev. Lett., 125:260505, Dec 2020. \ No newline at end of file diff --git a/cmake/FindCPLEX.cmake b/cmake/FindCPLEX.cmake new file mode 100644 index 0000000..1718a82 --- /dev/null +++ b/cmake/FindCPLEX.cmake @@ -0,0 +1,44 @@ + +#CPLEX +#set(ENV{CPLEX_ROOT} "/logiciels/cplex127/") + + find_path(CPLEX_INCLUDE_DIR + ilcplex/cplex.h + PATHS $ENV{CPLEX_ROOT}/cplex/include/) + + find_library(CPLEX_LIBRARY + libcplex.a + PATHS $ENV{CPLEX_ROOT}/cplex/lib/x86-64_linux/static_pic) + + find_library(CPLEX_CXX_LIBRARY + libilocplex.a + PATHS $ENV{CPLEX_ROOT}/cplex/lib/x86-64_linux/static_pic) + + find_path(CPLEX_LIBRARY_DIRS + NAMES libcplex.a + PATHS $ENV{CPLEX_ROOT}/cplex/lib/x86-64_linux/static_pic) + + +# Concert + + find_path(CONCERT_INCLUDE_DIR + ilconcert/cplexconcertdoc.h + PATHS $ENV{CPLEX_ROOT}/concert/include) + + find_library(CPLEX_LIBRARY_CONCERT + libconcert.a + PATHS $ENV{CPLEX_ROOT}/concert/lib/x86-64_linux/static_pic) + + find_path(CPLEX_LIBRARY_CONCERT_DIRS + libconcert.a + PATHS $ENV{CPLEX_ROOT}/concert/lib/x86-64_linux/static_pic) + + add_definitions("-D_CPLEX_FOUND") + mark_as_advanced(CPLEX_LIBRARY CPLEX_INCLUDE_DIR CPLEX_LIBRARY_DIRS CPLEX_LIBRARY_CONCERT) + set(CPLEX_LIBRARIES ${CPLEX_CXX_LIBRARY} ${CPLEX_LIBRARY}) + +if (NOT ${CPLEX_INCLUDE_DIR} MATCHES "CPLEX_INCLUDE_DIR_NOTFOUND") + message(STATUS "CPLEX_INCLUDE_DIR=${CPLEX_INCLUDE_DIR}") +else() + message(SEND_ERROR "CPLEX_INCLUDE_DIR not found") +endif() diff --git a/cmake/FindNLopt.cmake b/cmake/FindNLopt.cmake new file mode 100644 index 0000000..cfd9c30 --- /dev/null +++ b/cmake/FindNLopt.cmake @@ -0,0 +1,38 @@ +# FindNLopt.cmake + +# Locate the NLopt library and headers +# This module defines the following variables: +# NLOPT_FOUND, if false, do not try to use NLopt +# NLOPT_INCLUDE_DIRS, where to find nlopt.h, etc. +# NLOPT_LIBRARIES, the libraries to link against to use NLopt +# NLOPT_LIBRARY_DIRS, the directories containing the libraries + +find_path(NLOPT_INCLUDE_DIR + NAMES nlopt.h + PATHS ${NLopt_INSTALL_DIR}/include/ + /usr/local/lib + /usr/lib +) + +find_library(NLOPT_LIBRARY + NAMES nlopt + PATHS ${NLopt_INSTALL_DIR}/lib/ + /usr/local/lib + /usr/lib +) + +# Handle the QUIETLY and REQUIRED arguments and set NLOPT_FOUND to TRUE if all listed variables are TRUE +include(FindPackageHandleStandardArgs) +find_package_handle_standard_args(NLopt REQUIRED_VARS NLOPT_INCLUDE_DIR NLOPT_LIBRARY) +message(STATUS "JE CHERCHE NLOPTs") +message(STATUS ${NLOPT_INCLUDE_DIR}) +message(STATUS ${NLOPT_LIBRARY}) +message(STATUS ${NLopt_INSTALL_DIR}) + +if(NLOPT_FOUND) + set(NLOPT_INCLUDE_DIRS ${NLOPT_INCLUDE_DIR}) + set(NLOPT_LIBRARIES ${NLOPT_LIBRARY}) + set(NLOPT_LIBRARY_DIRS ${NLopt_INSTALL_DIR}/lib) +else() + message(FATAL_ERROR "Could not find NLopt") +endif() diff --git a/coloring/Branching.cpp b/coloring/Branching.cpp new file mode 100644 index 0000000..aa46c84 --- /dev/null +++ b/coloring/Branching.cpp @@ -0,0 +1,98 @@ +// +// Created by margarita on 09/12/22. +// +#ifdef QB_ENABLE_SCIP +#include "Branching.h" +#include "Vardata.h" +#include "Probdata.h" +#include "ConstraintHandler.h" + +using NodePair = struct nodePair{ + int u; + int v; +}; + +NodePair find_branching_constraint(Scip* scip, SCIP_VAR** fractional_vars, SCIP_Real* fractional_values, int nfractional, int node_number){ + + vector> pair_values(node_number, vector(node_number, 0)); // An array containing sum of fractional + + //Fill in the table + for(int i = 0; i < nfractional; i++){ + + SCIP_Real val = fractional_values[i]; + + //Get the corresponding independent set + Vardata* vardata = dynamic_cast(SCIPgetObjVardata(scip, fractional_vars[i])); + N_CONTAINER independent_set = vardata->get_independent_set(); + + for(const auto& u : independent_set){ + for(const auto& v: independent_set) + pair_values[u][v] += val; + } + } + + //Find the branching nodes in the graph + NodePair branching_pair = {-1, 1}; + SCIP_Real value, bestvalue = 0; + + for(int i = 0; i < node_number; i++) + for(int j = i+1; j < node_number; j++){ + + //Measure the "fractionality" of the pair interaction + value = MIN(pair_values[i][j], 1 - pair_values[i][j]); + + if(value > bestvalue) + //Check if one node i (or j) is not precisely covered by a subset of variables all covering the variable j (or i) + //Avoids getting an unfeasible problem or merging already merged nodes + if(!SCIPisEQ(scip, pair_values[i][j], pair_values[i][i]) && !SCIPisEQ(scip, pair_values[i][j], pair_values[j][j]) ) + { + bestvalue = value; + branching_pair = {i, j}; + } + } + + return branching_pair; +} + +SCIP_RETCODE Branching::scip_execlp(SCIP *scip, SCIP_BRANCHRULE *branchrule, unsigned int allowaddcons, SCIP_RESULT *result) { + + *result = SCIP_DIDNOTRUN; + + //get the problem data + Probdata* probdata = dynamic_cast(SCIPgetObjProbData(scip)); + + SCIP_VAR** fractional_vars; //stores fractional variables + SCIP_Real* fractional_values; //stores values of non-integral variables + + int n_fractional; // number of fractional values with maximal priority + + SCIP_CALL(SCIPgetLPBranchCands(scip, &fractional_vars, NULL, &fractional_values, NULL, &n_fractional, NULL)); + + NodePair branching_pair = find_branching_constraint(scip, fractional_vars, fractional_values, n_fractional, probdata->get_node_number()); + + SCIP_NODE *childsame, *childdiffer; + SCIP_CONS *conssame, *consdiffer; + + // create the branch-and-bound tree child nodes of the current node + SCIP_CALL( SCIPcreateChild(scip, &childsame, 0.0, SCIPgetLocalTransEstimate(scip)) ); + SCIP_CALL( SCIPcreateChild(scip, &childdiffer, 0.0, SCIPgetLocalTransEstimate(scip)) ); + + // create corresponding constraints + SCIP_CALL( createConsSamediff(scip, &conssame, "same", branching_pair.u, branching_pair.v, MERGE, childsame, TRUE) ); + SCIP_CALL( createConsSamediff(scip, &consdiffer, "differ", branching_pair.u, branching_pair.v, SPLIT, childdiffer, TRUE) ); + + // add constraints to nodes + SCIP_CALL( SCIPaddConsNode(scip, childsame, conssame, NULL) ); + SCIP_CALL( SCIPaddConsNode(scip, childdiffer, consdiffer, NULL) ); + + // release constraints + SCIP_CALL( SCIPreleaseCons(scip, &conssame) ); + SCIP_CALL( SCIPreleaseCons(scip, &consdiffer) ); + + *result = SCIP_BRANCHED; + + return SCIP_OKAY; + + +} +#endif // QB_ENABLE_SCIP \ No newline at end of file diff --git a/coloring/Branching.h b/coloring/Branching.h new file mode 100644 index 0000000..2c69611 --- /dev/null +++ b/coloring/Branching.h @@ -0,0 +1,36 @@ +// +// Created by margarita on 09/12/22. +// + +#ifdef QB_ENABLE_SCIP +#include "objscip/objbranchrule.h" + +#ifndef QUANTUM_BNP_BRANCHING_H +#define QUANTUM_BNP_BRANCHING_H + +#define BRANCHRULE_NAME "RyanFoster" +#define BRANCHRULE_DESC "Ryan-Foster branching rule" +#define BRANCHRULE_PRIORITY 50000 //Set high priority to impose the rule +#define BRANCHRULE_MAXDEPTH -1 //Apply the branching rule at all nodes (independently of depth) +#define BRANCHRULE_MAXBOUNDDIST 1.0 //Default distance from dual bound to primal bound + +using namespace scip; + +class Branching : public ObjBranchrule{ + +public: + Branching(SCIP* scip): ObjBranchrule(scip, BRANCHRULE_NAME, BRANCHRULE_DESC, BRANCHRULE_PRIORITY, BRANCHRULE_MAXDEPTH, BRANCHRULE_MAXBOUNDDIST){}; + + /**A branching method implementing Ryan-Foster Rule + * + * @param scip + * @param branchrule + * @param allowaddcons + * @param result + * @return + */ + SCIP_DECL_BRANCHEXECLP(scip_execlp) override; +}; + +#endif +#endif //QUANTUM_BNP_BRANCHING_H diff --git a/coloring/ConstraintHandler.cpp b/coloring/ConstraintHandler.cpp new file mode 100644 index 0000000..e93309d --- /dev/null +++ b/coloring/ConstraintHandler.cpp @@ -0,0 +1,133 @@ +// +// Created by margarita on 11/12/22. +// +#ifdef QB_ENABLE_SCIP +#include "ConstraintHandler.h" +#include "Probdata.h" +#include "Vardata.h" + +struct SCIP_ConsData { + int u; + int v; + ConsType type; // MERGE or SPLIT + + //Supplementary information that allows to avoid unnecessary efficient propagation + int n_propagated_vars; // How many variables there were when the constraint was propagated the last time + bool is_propagated; // Indicates if the constraint was already propagated + SCIP_NODE* node; // the node to which the constraint is sticking +}; + +SameDiff recover_constraint_characteristic(SCIP_CONS* cons){ + SCIP_ConsData* consdata = SCIPconsGetData(cons); + return {consdata->u, consdata->v, consdata->type}; +} + +SCIP_RETCODE ConstraintHandler::scip_active(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *cons) { + + Probdata *probdata = dynamic_cast(SCIPgetObjProbData(scip)); + SCIP_CONSDATA *consdata = SCIPconsGetData(cons); + + // Repropagate the constraint if itwas not propagated to all variables + if (consdata->n_propagated_vars != probdata->get_nvars()) { + consdata->is_propagated = false; + SCIP_CALL(SCIPrepropagateNode(scip, consdata->node)); + } + return SCIP_OKAY; +} + +SCIP_RETCODE ConstraintHandler::scip_deactive(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *cons) { + + Probdata *probdata = dynamic_cast(SCIPgetObjProbData(scip)); + SCIP_CONSDATA *consdata = SCIPconsGetData(cons); + + consdata->n_propagated_vars = probdata->get_nvars(); + return SCIP_OKAY; +} + +SCIP_RETCODE ConstraintHandler::scip_prop(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, int nusefulconss, + int nmarkedconss, SCIP_PROPTIMING proptiming, SCIP_RESULT *result) { + + *result = SCIP_DIDNOTFIND; //Method failed finding anything + Probdata* probdata = dynamic_cast(SCIPgetObjProbData(scip)); + vector variables = probdata->get_vars(); + + SCIP_Bool fixed; + SCIP_Bool infeasible; + SCIP_Bool cutoff = FALSE; + + int nfixed = 0; + + //Propagate each constraint in conss if it's not propagated + for(int i = 0; i< nconss; i++){ + + SCIP_CONSDATA * consdata = SCIPconsGetData(conss[i]); + ConsType type = consdata->type; + + if(! consdata->is_propagated){ + for(int v = consdata->n_propagated_vars; v < variables.size(); v++) { + + //If the variable can't have non-zero value we can scip it + if( SCIPvarGetUbLocal(variables[v]) < 0.5 ) + continue; + + Vardata *vardata = dynamic_cast (SCIPgetObjVardata(scip, variables[v])); + bool u_covered = vardata->covers(consdata->u); + bool v_covered = vardata->covers(consdata->v); + + if (type == MERGE && u_covered != v_covered || type == SPLIT && u_covered && v_covered){ + nfixed++; + SCIP_CALL( SCIPfixVar(scip, variables[v], 0.0, &infeasible, &fixed)); + cutoff = cutoff || infeasible; + } + } + + //If the problem becomes unsatisfiable because of the constraint conflict the propagation is stopped + if( cutoff ) { + *result = SCIP_CUTOFF; + break; + } + //Otherwise the constraint was successfully propagated + else { + consdata->is_propagated = true; + consdata->n_propagated_vars = variables.size(); + if (nfixed > 0) + *result = SCIP_REDUCEDDOM; + } + } + } + return SCIP_OKAY; +} + +SCIP_RETCODE ConstraintHandler::scip_trans(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *sourcecons, SCIP_CONS **targetcons) { + + //Copies the source constraint to a transformed constraint + SCIP_CONSDATA * sourcedata = SCIPconsGetData(sourcecons); + SCIP_CONSDATA * targetdata; + SCIP_CALL (SCIPallocBlockMemory(scip, &targetdata)); + *targetdata = *sourcedata; + + SCIPcreateCons(scip, targetcons, SCIPconsGetName(sourcecons), conshdlr, targetdata, + SCIPconsIsInitial(sourcecons), SCIPconsIsSeparated(sourcecons), SCIPconsIsEnforced(sourcecons), + SCIPconsIsChecked(sourcecons), SCIPconsIsPropagated(sourcecons), SCIPconsIsLocal(sourcecons), + SCIPconsIsModifiable(sourcecons), SCIPconsIsDynamic(sourcecons), SCIPconsIsRemovable(sourcecons), + SCIPconsIsStickingAtNode(sourcecons)); +} + +SCIP_RETCODE ConstraintHandler::scip_delete(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *cons, SCIP_CONSDATA **consdata) { + SCIPfreeBlockMemory(scip, consdata); + return SCIP_OKAY; +} + +SCIP_RETCODE createConsSamediff(SCIP* scip, SCIP_CONS** cons, const char* name, int u, int v, ConsType type, SCIP_NODE* node,SCIP_Bool local){ + SCIP_CONSHDLR * handler = SCIPfindConshdlr(scip, CONSHDLR_NAME); + SCIP_CONSDATA * consdata; + + SCIP_CALL (SCIPallocBlockMemory(scip, &consdata)); + *consdata = {u, v, type, 0, FALSE, node}; + + SCIP_CALL( SCIPcreateCons(scip, cons, name, handler, consdata, FALSE, FALSE, FALSE, FALSE, TRUE, + local, FALSE, FALSE, FALSE, TRUE) ); + + return SCIP_OKAY; +}; + #endif // QB_ENABLE_SCIP \ No newline at end of file diff --git a/coloring/ConstraintHandler.h b/coloring/ConstraintHandler.h new file mode 100644 index 0000000..fc5072c --- /dev/null +++ b/coloring/ConstraintHandler.h @@ -0,0 +1,127 @@ +// +// Created by margarita on 11/12/22. +// + +#ifndef QUANTUM_BNP_CONSTRAINTHANDLER_H +#define QUANTUM_BNP_CONSTRAINTHANDLER_H + +#ifdef QB_ENABLE_SCIP + +#include "scip/scip.h" +#include "objscip/objconshdlr.h" + + +#define CONSHDLR_NAME "SameDiff" +#define CONSHDLR_DESC "stores the local branching decisions" +#define CONSHDLR_SEPAPRIORITY 0 // priority of the constraint handler for separation (never called) +#define CONSHDLR_ENFOPRIORITY 0 // priority of the constraint handler for constraint enforcing (goes after the set covering) +#define CONSHDLR_CHECKPRIORITY 9999999 // priority of the constraint handler for checking feasibility (the check is trivial) +#define CONSHDLR_SEPAFREQ -1 // frequency for spearation (constraint not used) +#define CONSHDLR_PROPFREQ 1 // frequency for propagating domains +#define CONSHDLR_EAGERFREQ 1 // frequency for using all instead of only the useful constraints in separation +#define CONSHDLD_MAXPREROUND 1 // maximal number of presolving rounds the constraint handler participates in +#define CONSHDLR_DELAYSEPA FALSE // should separation method be delayed, +#define CONSHDLR_DELAYPROP FALSE // should propagation method be delayed, if other propagators found reductions? +#define CONSHDLR_NEEDSCONS TRUE // should the constraint handler be skipped, if no constraints are available? +#define CONSHDLR_PROP_TIMING SCIP_PROPTIMING_BEFORELP //Propagate the constraint before the relaxation is solved +#define CONSHDLR_PRESOLTIMING SCIP_PRESOLTIMING_EXHAUSTIVE + +using namespace scip; + +enum ConsType +{ + SPLIT = 0, //corresponding nodes should be in different independent sets + MERGE = 1 //corresponding nodes should be in the same independent set +}; + +using SameDiff = struct SameDiff { + int u; + int v; + ConsType type; +}; + +class ConstraintHandler : public ObjConshdlr{ + +public: + ConstraintHandler(Scip* scip) : ObjConshdlr(scip, CONSHDLR_NAME, CONSHDLR_DESC, + CONSHDLR_SEPAPRIORITY, CONSHDLR_ENFOPRIORITY, CONSHDLR_CHECKPRIORITY, + CONSHDLR_SEPAFREQ, CONSHDLR_PROPFREQ, CONSHDLR_EAGERFREQ, + CONSHDLD_MAXPREROUND, + CONSHDLR_DELAYSEPA, CONSHDLR_DELAYPROP, + CONSHDLR_NEEDSCONS, + CONSHDLR_PROP_TIMING, CONSHDLR_PRESOLTIMING) {}; + + /** Activated the constraint + * + * if the constraint is not already propagated to all variables repropagates it + * + * @param scip + * @param conshdlr + * @param cons + * @return + */ + virtual SCIP_DECL_CONSACTIVE(scip_active) override; + + /** Activate the constraint + * + * If it is not propagated to all existing variables - launch the propagation + * + * @param scip + * @param conshdlr + * @param cons + * @return + */ + virtual SCIP_DECL_CONSDEACTIVE(scip_deactive) override; + + /** Domain propagation method + * + * @param scip + * @param conshdlr + * @param conss + * @param nconss + * @param nusefulconss + * @param nmarkedconss + * @param proptiming + * @param result store the result of propagation, which may be the domain reduction (SCIP_REDUCEDDOM), the insatisfability (SCIP_CUTOFF) + * @return + */ + virtual SCIP_DECL_CONSPROP(scip_prop) override; + + /**Transform constraint data into data from transformed problem + * + * @param scip + * @param conshdlr + * @param sourcecons + * @param targetcons + * @return + */ + virtual SCIP_DECL_CONSTRANS(scip_trans) override; + + //Methods are nor used in for the Handler, however, the definition is needed as they are virtual + virtual SCIP_DECL_CONSDELETE(scip_delete) override; + virtual SCIP_DECL_CONSCHECK(scip_check) override { *result = SCIP_FEASIBLE; return SCIP_OKAY;}; + virtual SCIP_DECL_CONSENFOLP(scip_enfolp) override { *result = SCIP_FEASIBLE; return SCIP_OKAY;}; + virtual SCIP_DECL_CONSENFOPS(scip_enfops) override { *result = SCIP_FEASIBLE; return SCIP_OKAY;}; + virtual SCIP_DECL_CONSLOCK(scip_lock) override { return SCIP_OKAY;}; + virtual SCIP_DECL_CONSSEPASOL(scip_sepasol) override { return SCIP_OKAY;}; + +}; + +SameDiff recover_constraint_characteristic(SCIP_CONS* cons); + + +/** Creates a new SameDiff constraint + * + * @param scip + * @param cons pointer to add constraint + * @param name + * @param u first node + * @param V second node + * @param type MERGE of SPLIT + * @param node node that stores the constraint + * @param local + * @return + */ +SCIP_RETCODE createConsSamediff(SCIP* scip, SCIP_CONS** cons, const char* name, int u, int v, ConsType type, SCIP_NODE* node,SCIP_Bool local); +#endif //QB_ENABLE_SCIP +#endif //QUANTUM_BNP_CONSTRAINTHANDLER_H diff --git a/coloring/Pricer.cpp b/coloring/Pricer.cpp new file mode 100644 index 0000000..d5b3650 --- /dev/null +++ b/coloring/Pricer.cpp @@ -0,0 +1,129 @@ +// +// Created by margarita on 11/12/22. +// +#ifdef QB_ENABLE_SCIP +#include +#include "scip/cons_setppc.h" + +#include "Pricer.h" +#include "Vardata.h" +#include "ConstraintHandler.h" +#include "Probdata.h" + + +SCIP_RETCODE Pricer::add_branching_constraints() { + if(branching_accounted) + throw "Branching constraint was already integrated"; + + local_graph = *initial_graph; + + auto constraint_set = SCIPconshdlrGetConss(conshdlr); + auto n_conss = SCIPconshdlrGetNConss(conshdlr); + + SCIP_CONS* constraint; + + for(int i = 0; i < n_conss; i++){ + constraint = constraint_set[i]; + + if(!SCIPconsIsActive(constraint)) + continue; + + SameDiff* cons_data = (SameDiff *) SCIPconsGetData(constraint); + + if(cons_data->type == MERGE) + local_graph.merge_nodes(cons_data->u, cons_data->v); + else if(cons_data->type == SPLIT) + local_graph.split_nodes(cons_data->u, cons_data->v); + else + return SCIP_INVALIDDATA; + } + + branching_accounted = true; + return SCIP_OKAY; +} + +SCIP_RETCODE Pricer::add_MWIS_variable_to_SCIP(SCIP* scip, const N_CONTAINER& independent_set) { + SCIP_VAR* var; + ObjVardata* vardata = new Vardata(independent_set); //TODO when free? + string varname = "l_" + to_string(counter); + counter++; + + SCIP_CALL(SCIPcreateObjVar(scip, &var, varname.c_str(), 0.0, 1.0, 1.0, SCIP_VARTYPE_BINARY, false, true, vardata, true)); + + //Change the upper bound to lazy as the objective function already implies it + SCIP_CALL( SCIPchgVarUbLazy(scip, var, 1.0)); + + //Add the variable to the formulation, modifies the objective function + SCIP_CALL( SCIPaddPricedVar(scip, var, 1.0)); + + //Add the variable to constraints + for(const auto& u: independent_set) + SCIP_CALL( SCIPaddCoefSetppc(scip, covering_constraints[u], var)); + + SCIP_CALL( SCIPreleaseVar(scip, &var) ); + + return SCIP_OKAY; +} + +SCIP_DECL_PRICERINIT(Pricer::scip_init){ + SCIP_EVENTHDLR * eventhdlr = SCIPfindEventhdlr(scip, EVENTHDLR_NAME); + SCIP_CALL( SCIPcatchEvent(scip, SCIP_EVENTTYPE_VARADDED, eventhdlr, NULL, NULL) ); + + for(auto & cons : covering_constraints){ + SCIP_CONS * old_cons = cons; + + //release original constraint + //SCIP_CALL(SCIPreleaseCons(scip, &cons)); + + //get the transformed constraint + SCIP_CALL(SCIPgetTransformedCons(scip, old_cons, &cons)); + } + return SCIP_OKAY; +} + +SCIP_DECL_PRICERREDCOST(Pricer::scip_redcost){ + if(!branching_accounted) + add_branching_constraints(); + + //Initialize weights from dual values + + WTYPE dual; + local_graph.set_weights_to_zero(); + for(int u = 0; u < covering_constraints.size(); u++){ + dual = SCIPgetDualsolSetppc(scip, covering_constraints[u]); + local_graph.add_node_weight(u, dual); + } + + //Find an improving MWIS if it exists + + bool found = false; // becomes true when heuristic or exact method finds an improving variable + WTYPE cutoff = 1.0 + SCIPepsilon(scip); // If the independent set has a weight > cutoff then it improves the solution + + N_CONTAINER mwis; + WTYPE mwis_value = 0; + + //Search for an improving independent se(t + found = greedyMWIS(local_graph, mwis, mwis_value, cutoff); + if(!found) { + found = quantumMWIS(local_graph, mwis, mwis_value, cutoff); + rqaoa_found += found; +// cout << "RQAOA found an IS of weight: " << mwis_value << endl; + } + if(!found){ + found = cplexMWIS(local_graph, mwis, mwis_value, cutoff); + exact_found += found; +// cout << "CPLEX found an IS of weight: " << mwis_value << endl; + } + if(found) { + mwis = local_graph.recover_all_merged_to(mwis); + if (is_independent_set(*initial_graph, mwis)) + add_MWIS_variable_to_SCIP(scip, mwis); + else + cout << "The pricing found an infeasible solution"; + } + else branching_accounted = false; // As the improving variable was not found, the branching occurs before the next execution + + (*result) = SCIP_SUCCESS; + return SCIP_OKAY; +} +#endif diff --git a/coloring/Pricer.h b/coloring/Pricer.h new file mode 100644 index 0000000..58ddcf9 --- /dev/null +++ b/coloring/Pricer.h @@ -0,0 +1,114 @@ +// +// Created by margarita on 11/12/22. +// + +#ifndef QUANTUM_BNP_PRICER_H +#define QUANTUM_BNP_PRICER_H + +#ifdef QB_ENABLE_SCIP + #include "scip/scip.h" + #include "objscip/objpricer.h" +#endif + +#include "../mwis/mwis.h" + + +#define PRICER_NAME "MWIS" +#define PRICER_DESC "Find an independent set with reduced cost > 1" +#define PRICER_PRIORITY 0 // If multiple pricers are defined they are called in decreasing priority order, in our code there is only ine pricer +#define PRICER_DELAY true // Pricer is called if all existing variables have negative reduced cost + + +class Pricer : public scip::ObjPricer { + + int counter; // Used to name priced variables + const Graph* initial_graph; //doesn't change during execution + + vector covering_constraints; //initial constraints in the formulation assuring that each node is covered + SCIP_CONSHDLR * conshdlr; + + bool branching_accounted; // Is true if we had prepared the correct local graph + Graph local_graph; // Graph with merged and split vertices defined by branching constraints + + // Logging information + int rqaoa_found; // how often qaoa manages to find an improving variable + int exact_found; // how often the exact method finds an improving variable + +private: + /** Modifies the local Pricer graph at each node of the Branch & Bound tree + * + * Constructs a local graph with merged and split nodes from the samediff constraints + * * + * @param conshdlr + * @return + * @throw TODO an error if called when the branching constraints were already accounted + */ + SCIP_RETCODE add_branching_constraints(); + + /** Create and add a variable corresponding to an imrpoving independent set + * + * @param independent_set + * @return + */ + SCIP_RETCODE add_MWIS_variable_to_SCIP(SCIP* scip, const N_CONTAINER& independent_set); +public: + + Pricer (SCIP* scip, const Graph* _initial_graph, const vector& constraints) : + counter(0), rqaoa_found(0), exact_found(0), + initial_graph(_initial_graph), + covering_constraints(constraints), + conshdlr(SCIPfindConshdlr(scip, "SameDiff")), + ObjPricer(scip, PRICER_NAME, PRICER_DESC, PRICER_PRIORITY, PRICER_DELAY) {}; + + /** Initialize the Pricer after the problem was transformed + * + * Resets constraints to the constraints from the transformed problems + * Transformed problem is a copy of the initial problem created during the solving process + * All modifications performed by pricing are applied to the transformed problem + * + * @param scip + * @param pricer + * @return + */ + SCIP_DECL_PRICERINIT(scip_init) override; + + /** Find a reduced variable of negative cost + * + * @param scip + * @param pricer + * @param lowerbound + * @param stopearly + * @param result refers to SCIP_SUCCESS if an improving variable is found, otherwise is SCIP_DIDNOTRUN + * @note if an imrpoving variable is not found, set branching_accounted to false + * @return + */ + SCIP_DECL_PRICERREDCOST(scip_redcost) override; + + /** The linear program should never become infeasible after the branching + * + * If the method is called something went wrong, abort the execution + * + * @param scip + * @param pricer + * @param result + * @throw TODO + * @return + */ + SCIP_DECL_PRICERFARKAS(scip_farkas) { + SCIPABORT(); + } + + /** Print the RQAOA success rate*/ + void print_success_rate(){ + cout << "RQAOA success rate is: " << rqaoa_found / (rqaoa_found + exact_found) << endl; + } +}; + + + + + + + + +#endif //QUANTUM_BNP_PRICER_H diff --git a/coloring/Probdata.cpp b/coloring/Probdata.cpp new file mode 100644 index 0000000..43fdee2 --- /dev/null +++ b/coloring/Probdata.cpp @@ -0,0 +1,171 @@ +// +// Created by margarita on 11/12/22. +// +#ifdef QB_ENABLE_SCIP +#include +#include "../Graph.h" +#include "Probdata.h" +#include "Vardata.h" +#include "algorithm" + + + + +vector dsatur(const Graph* graph, int& n_colors) +{ + n_colors = 0; + int node_number = graph->get_node_number(); + vector candidate_color(node_number, 0); // All colors smaller than candidate color are assumed to be unavailable for the node + + vector forbidden_colors(node_number); // Colors greater than candidate_color[u] that are forbidden for the node u + + vector sat_degree(node_number, 0); // Saturation degree - how many neighbors of the node are already colored + + N_CONTAINER uncolored; + for(N_ID u = 0; u < node_number; u++) uncolored.insert(u); + + //A comparator that allows at each step to select a node with maximal saturated degree, ties are broken in favor of nodes with higher degrees in the graph + auto comp = [&sat_degree, &graph](N_ID u, N_ID v){ + if (sat_degree[u] < sat_degree[v]) + return true; + else if (sat_degree[u] == sat_degree[v]) + return graph->get_degree(u) < graph->get_degree(v); + return false; + }; + + while(!uncolored.empty()) + { + auto node_to_color = std::max_element(uncolored.begin(), uncolored.end(), comp); + int used_color = candidate_color[*node_to_color]; + if(used_color > n_colors) + n_colors = used_color; + + auto neighbors = graph->get_neighbors(*node_to_color); + for(const auto & u : neighbors) + { + if(uncolored.count(u)) + { + sat_degree[u]++; + if (candidate_color[u] > used_color) + continue; + if (candidate_color[u] < used_color) + { + forbidden_colors[u].insert(used_color); + continue; + } + if (candidate_color[u] == used_color) + candidate_color[u]++; + auto it = forbidden_colors[u].begin(); + while(it != forbidden_colors[u].end() && candidate_color[u] == *it) + { + it = forbidden_colors[u].erase(it); + candidate_color[u]++; + } + } + } + uncolored.erase(node_to_color); + } + n_colors++; + return candidate_color; +} + +SCIP_RETCODE Probdata::initialize_cons(Scip *scip) { + + string cons_name = "node_"; + for(int u = 0; u < initial_graph->get_node_number(); u++){ + string cons_name = "node_" + to_string(u); + SCIP_CONS* cover_cons; + + SCIP_CALL( SCIPcreateConsBasicSetcover(scip, &cover_cons, cons_name.c_str(), 0, NULL)); + SCIP_CALL( SCIPsetConsModifiable(scip, cover_cons, TRUE)); + SCIP_CALL( SCIPaddCons(scip, cover_cons)); + covering_constraints.push_back(cover_cons); + + SCIP_CALL( SCIPreleaseCons(scip, &cover_cons)); + } + return SCIP_OKAY; +} + +SCIP_RETCODE Probdata::initialize_vars(Scip *scip) { + int n_colors; + vector dsatur_coloring = dsatur(initial_graph, n_colors); + + for(int c = 0; c < n_colors; c++){ + string var_name = "in_var_" + to_string(c); + SCIP_VAR * var; + Vardata* vardata = new Vardata(); //TODO when free? + + SCIP_CALL( SCIPcreateObjVar(scip, &var, var_name.c_str(), 0.0, 1.1, 1.0, SCIP_VARTYPE_BINARY, true, true, vardata, true)); + SCIP_CALL( SCIPchgVarUbLazy(scip, var, 1.0)); //The upper bound is already enforced by the objective function + + SCIP_CALL( SCIPaddVar(scip, var)); + + //Add the variable to constraints corresponding to nodes covered by it + N_CONTAINER c_set; + for(int u = 0; u < initial_graph->get_node_number(); u++){ + if (dsatur_coloring[u] == c) { + SCIP_CALL(SCIPaddCoefSetppc(scip, covering_constraints[u], var)); + c_set.insert(u); + } + } + vardata->set_independent_set(c_set); //Add the variable data + + variables.push_back(var); + + SCIP_CALL( SCIPreleaseVar(scip, &var)); + } +} +Probdata::Probdata(const Graph* graph): ObjProbData() { + initial_graph = new Graph(*graph); +}; + +SCIP_RETCODE Probdata::scip_trans(SCIP *scip, ObjProbData **objprobdata, unsigned int *deleteobject) { + Probdata* transdata = new Probdata(initial_graph); + + // for each variable push its transformed version to the transformed problem data + transdata->variables.clear(); + + for(auto& orig_var: variables){ + SCIP_VAR * transvar; + SCIPtransformVar(scip, orig_var, &transvar); + transdata->variables.push_back(transvar); + SCIPreleaseVar(scip, &transvar); + } + + //for each constraint push its transformed version to the transformed problem data + SCIP_CONS * transcons; + for (auto& orig_cons : covering_constraints){ + + SCIPtransformCons(scip, orig_cons, &transcons); + transdata->covering_constraints.push_back(transcons); + } + + *deleteobject = FALSE; //TODO + *objprobdata = transdata; + return SCIP_OKAY; +} + +SCIP_RETCODE Probdata::scip_deltrans(SCIP *scip) { + for(auto & var: variables) { + SCIP_CALL(SCIPreleaseVar(scip, &var)); + } + + return SCIP_OKAY; +} + +SCIP_RETCODE Probdata::scip_delorig(SCIP *scip) { + for(auto & var: variables) + SCIP_CALL(SCIPreleaseVar(scip, &var)); + + return SCIP_OKAY; +} + +SCIP_RETCODE EventAddedVar::scip_exec(SCIP *scip, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENT *event, SCIP_EVENTDATA *eventdata) { + Probdata* probdata = dynamic_cast(SCIPgetObjProbData(scip)); + SCIP_VAR* var_to_add = SCIPeventGetVar(event); + probdata->addVar(scip, var_to_add); + + return SCIP_OKAY; +} + +#endif //QB_ENABLE_SCIP \ No newline at end of file diff --git a/coloring/Probdata.h b/coloring/Probdata.h new file mode 100644 index 0000000..905ec0a --- /dev/null +++ b/coloring/Probdata.h @@ -0,0 +1,103 @@ +// +// Created by margarita on 11/12/22. +// +#ifdef QB_ENABLE_SCIP +#include "../Graph.h" +#ifndef QUANTUM_BNP_PROBDATA_H +#define QUANTUM_BNP_PROBDATA_H + +#include "ConstraintHandler.h" +#include "scip/scip.h" +#include "objscip/objprobdata.h" +#include "objscip/objeventhdlr.h" + +#define EVENTHDLR_NAME "Added Variable" +#define EVENTHDLR_DESC "Event handler for catching added variables" + + +using namespace scip; + +class Probdata : public ObjProbData { + vector variables; + vector covering_constraints; + Graph* initial_graph; + + +public: + Probdata(const Graph* graph); + ~Probdata() { delete initial_graph; }; + + /** Create covering constraint for each node in the initial_graph + * + * @param scip + * @return + */ + SCIP_RETCODE initialize_cons(Scip* scip); + + /** Add initial variables that assures the existence of a feasible solution + * + * Creates and adds initial variables to constrains. Uses DSATUR greedy heuristic to compute colors. + * + * @param scip + * @return + */ + SCIP_RETCODE initialize_vars(Scip* scip); + + Graph* get_graph() const { return initial_graph; }; + int get_node_number() const { return initial_graph->get_node_number(); }; + int get_nvars() const { return variables.size(); }; + vector get_vars() const { return variables; }; + vector get_cons() const { return covering_constraints; }; + + //TODO + /** Initialize the transformed problem from the initial problem + * + * The method resets variables and constraints to transformed ones + * + * @param scip + * @param objprobdata where transformed problem is stored + * @param deleteobject If TRUE + * @return + */ + SCIP_RETCODE scip_trans(SCIP* scip, ObjProbData** objprobdata, SCIP_Bool* deleteobject) override; + + /** Add a newly created variable to probdata + * + * @param var_to_add + */ + SCIP_RETCODE addVar(Scip* scip, SCIP_VAR* var_to_add) { + SCIP_CALL( SCIPcaptureVar(scip, var_to_add) ); + variables.push_back(var_to_add); + + return SCIP_OKAY; + }; + + SCIP_RETCODE scip_deltrans(SCIP *scip) override; + + SCIP_RETCODE scip_delorig(SCIP *scip) override; +}; + +class EventAddedVar : public ObjEventhdlr{ + +public: + /** If any method (Pricer or initialization method) creates a variable it is added to the probdata + * + * @param scip + */ + EventAddedVar(SCIP* scip): ObjEventhdlr( scip, EVENTHDLR_NAME, EVENTHDLR_DESC){}; + SCIP_DECL_EVENTEXEC(scip_exec) override; +}; + +/** Dsatur greedy coloring method + * + * See https://www.geeksforgeeks.org/dsatur-algorithm-for-graph-coloring/ for details + * + * @param graph + * @param ncolors + * @return a vector with colors + * @note is called to obtain initial set of variables for which a feasble solution exist + */ +vector dstatur(const Graph* graph, int& ncolors); + +#endif +#endif //QUANTUM_BNP_PROBDATA_H diff --git a/coloring/Vardata.cpp b/coloring/Vardata.cpp new file mode 100644 index 0000000..2eb0c93 --- /dev/null +++ b/coloring/Vardata.cpp @@ -0,0 +1,5 @@ +// +// Created by margarita on 11/12/22. +// + +#include "Vardata.h" diff --git a/coloring/Vardata.h b/coloring/Vardata.h new file mode 100644 index 0000000..96166cf --- /dev/null +++ b/coloring/Vardata.h @@ -0,0 +1,36 @@ +// +// Created by margarita on 11/12/22. +// + +#ifndef QUANTUM_BNP_VARDATA_H +#define QUANTUM_BNP_VARDATA_H + +#ifdef QB_ENABLE_SCIP +#include "scip/scip.h" +#include "objscip/objvardata.h" + + +#include "../Graph.h" +using namespace scip; + +/** Stores the data related to each variable in formulation + * + */ +class Vardata : public ObjVardata{ + N_CONTAINER independent_set; +public: + Vardata(): independent_set(), ObjVardata() {}; + Vardata(const N_CONTAINER& IS): independent_set(IS), ObjVardata() {}; + void set_independent_set(const N_CONTAINER& IS) { independent_set = IS; }; + + N_CONTAINER get_independent_set() const { return independent_set; }; + + /** Check if an independent set covers the input node + * + * @param u + * @return + */ + bool covers(int u) const { return independent_set.count(u); }; +}; +#endif // QB_ENABLE_SCIP +#endif //QUANTUM_BNP_VARDATA_H diff --git a/coloring/coloring.cpp b/coloring/coloring.cpp new file mode 100644 index 0000000..d26ab9e --- /dev/null +++ b/coloring/coloring.cpp @@ -0,0 +1,94 @@ +// +// Created by margarita on 12/12/22. +// +#include +#ifdef QB_ENABLE_SCIP +#include "coloring.h" +#include "Probdata.h" +#include "ConstraintHandler.h" +#include "Branching.h" +#include "Pricer.h" +#include "scip/scipdefplugins.h" +#include "Vardata.h" + + +SCIP_RETCODE coloringBNP(const Graph& graph, vector& colors){ + SCIP * scip = NULL; + SCIP_CALL( SCIPcreate(&scip) ); + + Probdata* probdata = new Probdata(&graph); + SCIP_CALL( SCIPcreateObjProb(scip, "COLORING", probdata, true)); + + SCIP_CALL ( SCIPincludeDefaultPlugins(scip)); + + probdata->initialize_cons(scip); + probdata->initialize_vars(scip); + + ConstraintHandler* conshdlr = new ConstraintHandler(scip); + SCIP_CALL( SCIPincludeObjConshdlr(scip, conshdlr, true)); + + Branching* branching = new Branching(scip); + SCIP_CALL( SCIPincludeObjBranchrule(scip, branching, true)); + + //Event handler for addition of variable + EventAddedVar* eventhdlr = new EventAddedVar(scip); + SCIP_CALL( SCIPincludeObjEventhdlr(scip, eventhdlr, false)); + + Pricer* pricer = new Pricer(scip, &graph, probdata->get_cons()); + SCIP_CALL( SCIPincludeObjPricer(scip, pricer, true)); + SCIP_CALL ( SCIPactivatePricer(scip, SCIPfindPricer(scip, PRICER_NAME))); //Activates the pricer used in solution, deactivation is automatic + + // set the time limit + SCIP_CALL( SCIPsetRealParam(scip, "limits/time", TIME_LIMIT) ); + + // set verbosity level + SCIP_CALL( SCIPsetIntParam(scip,"display/verblevel",0)); + + // for column generation instances, disable restarts + SCIP_CALL( SCIPsetIntParam(scip,"presolving/maxrestarts",0) ); + + // turn off all separation algorithms + SCIP_CALL( SCIPsetSeparating(scip, SCIP_PARAMSETTING_OFF, TRUE) ); + + // set objective sense + SCIP_CALL( SCIPsetObjsense(scip, SCIP_OBJSENSE_MINIMIZE) ); + + // tell SCIP that the objective will be always integral + SCIP_CALL( SCIPsetObjIntegral(scip) ); + + SCIP_CALL( SCIPsolve(scip) ); + + SCIP_SOL * scip_solution = SCIPgetBestSol(scip); + + if (! scip_solution ) + throw "Solution not found!"; + else{ + int n_colors = 0; + + + //New variables are added only to a transformed problem, therefore probdata doesn't refer to an updated set of variables + Probdata* trans_probdata = dynamic_cast(SCIPgetObjProbData(scip)); + vector variables = trans_probdata->get_vars(); + + //Recover solution + for(auto& var: variables){ + SCIP_Real value = SCIPgetSolVal(scip, scip_solution, var); + if (SCIPisEQ(scip, value, 1.0)){ + Vardata* vardata = dynamic_cast(SCIPgetObjVardata(scip, var)); + for(const auto & u: vardata->get_independent_set()) + colors[u] = n_colors; + n_colors++; + } + } + /* for(int i = 0; i < variables.size(); i++){ + SCIPreleaseVar(scip, &variables[i]); + }*/ + cout << "Branch & Price found a coloring with " << n_colors << " colors." << endl; + pricer->print_success_rate(); + } + + SCIPfree(&scip); + return SCIP_OKAY; +}; + +#endif // QB_ENABLE_SCIP \ No newline at end of file diff --git a/coloring/coloring.h b/coloring/coloring.h new file mode 100644 index 0000000..a740257 --- /dev/null +++ b/coloring/coloring.h @@ -0,0 +1,22 @@ +// +// Created by margarita on 12/12/22. +// + +#ifndef QUANTUM_BNP_COLORING_H +#define QUANTUM_BNP_COLORING_H +#include "../Graph.h" +#ifdef QB_ENABLE_SCIP + #include "scip/scip.h" +#endif + +#define TIME_LIMIT 50000 // The upper bound on the Branch & Price runtime + +/** Color the nodes of the graph with Branch & Price + * + * @param graph + * @param colors vector to store the colors of nodes + * @return + */ +SCIP_RETCODE coloringBNP(const Graph& graph, vector& colors); + +#endif //QUANTUM_BNP_COLORING_H diff --git a/main.cpp b/main.cpp new file mode 100644 index 0000000..132c880 --- /dev/null +++ b/main.cpp @@ -0,0 +1,88 @@ +#include +#include "Graph.h" + +#include "mwis/mwis.h" + + +#ifdef QB_ENABLE_SCIP + #include "coloring/coloring.h" +#endif + +/** print the independent set in found by one of methods + * + * @param method heuristic or exact approach used to find the independent set + * @param value + * @param independent_set + */ +void print_mwis_result(const string& method, const WTYPE& value, const N_CONTAINER& independent_set){ + cout << method << " returned an independent set of value: " << value << endl; + cout << "The set is: "; + for(const auto& u: independent_set) + cout << u << " "; + cout << "\n" << endl; + return; +} + + +//TODO Throw exceptions on invalid input +int main(int argc, char* argv[]) { + if(argc < 3) { + cout << "Wrong command arguments. Minimum number of arguments = 3"; + return 1; + } + + string problem_name(argv[1]); + string instance_file(argv[2]); + + Graph graph; + graph.read_dimacs(instance_file); + + if(problem_name == "-MWIS") + { + if(argc < 4) { + cout << "Wrong command arguments for MWIS problem, minimum number of argument = 4 \n"; + return 1; + } + string method(argv[3]); + WTYPE weight = 0; + WTYPE cutoff = INF; + N_CONTAINER independent_set; + + if(method == "-greedy") { + greedyMWIS(graph, independent_set, weight, cutoff); + } + if(method == "-quantum") { + quantumMWIS(graph, independent_set, weight, cutoff); + } + #ifdef QB_ENABLE_CPLEX + if(method == "-cplex") { + cplexMWIS(graph, independent_set, weight, cutoff); + } + #endif + /* + if(method == "-sewell") { + sewellMWIS(graph, independent_set, weight, cutoff); + }*/ + + cout << "MWIS is independent: " << is_independent_set(graph, independent_set) << endl; + print_mwis_result(method, weight, independent_set); + } + + if(problem_name == "-COLORING") + { + #ifdef QB_ENABLE_SCIP + vector colors(graph.get_node_number(), 0); + coloringBNP(graph, colors); + + cout << "COLORING:"; + for(const auto &u: colors) + cout << " " << u; + cout << endl; + #else + std::cout << "WARNING you need to install and activate SCIP to use coloring problem" << endl; + #endif + + } + + return 0; +} diff --git a/mwis/LocalSearch.cpp b/mwis/LocalSearch.cpp new file mode 100644 index 0000000..87285f7 --- /dev/null +++ b/mwis/LocalSearch.cpp @@ -0,0 +1,108 @@ +// +// Created by margarita on 06/12/22. +// + +#include "LocalSearch.h" +#include + +#include "../Graph.h" + +void LocalSearch::init(N_CONTAINER& IS) { + active_nodes = IS; + deactivated_nodes = {}; + tightness = vector(graph->get_node_number(), 0); + for(const auto& u: active_nodes) + for(const auto& v: graph->get_neighbors(u)) + tightness[v]++; + for(const auto& u: graph->get_active_nodes()) + if(!active_nodes.count(u) && tightness[u] == 0) + free_nodes.insert(u); + to_maximal(); +} + +bool LocalSearch::find_swap(N_ID &exit, N_ID & enter1, N_ID & enter2) { + auto it = active_nodes.begin(); + while (it != active_nodes.end()) { + vector one_tight_neighbors{}; + N_ID u = *it; + for (const auto &v: graph->get_neighbors(u)) + if (tightness[v] == 1) + one_tight_neighbors.push_back(v); + + for (auto v = one_tight_neighbors.begin(); v != one_tight_neighbors.end(); v++) { + auto neighbors = graph->get_neighbors(*v); + auto w = v + 1; + auto v_neighbor = neighbors.begin(); + while (w != one_tight_neighbors.end() && v_neighbor != neighbors.end()) { + if (graph->get_node_weight(*w) + graph->get_node_weight(*v) >= graph->get_node_weight(u)) { + if (*w < *v_neighbor) break; + else if (*w == *v_neighbor) w++; + v_neighbor++; + } + else w++; + } + if (w != one_tight_neighbors.end()) { + exit = u; enter1 = *v; enter2 = *w; + return true; + } + } + it = active_nodes.erase(it); + deactivated_nodes.insert(u); + } + return false; +} + +void LocalSearch::remove_from_solution(const N_ID &u) { + if(!active_nodes.count(u)) + throw std::range_error("Can't remove vertex that is not in solution"); + for(const auto& v: graph->get_neighbors(u)) { + tightness[v]--; + if(tightness[v] == 0) + free_nodes.insert(v); + if(tightness[v] == 1) + { + auto it = find_if(deactivated_nodes.begin(), deactivated_nodes.end(), [this, v](const N_ID& u){return graph->has_edge(u, v);}); + if(it != deactivated_nodes.end()) + { + active_nodes.insert(*it); + deactivated_nodes.erase(it); + } + } + } + active_nodes.erase(u); +} + +void LocalSearch::add_to_solution(const N_ID &u) { + if(!free_nodes.count(u)) + throw std::range_error("Can't add vertex that is not free"); + for(const auto& v: graph->get_neighbors(u)) { + tightness[v]++; + free_nodes.erase(v); + } + free_nodes.erase(u); + active_nodes.insert(u); +} + + +void LocalSearch::to_maximal() { + while(!free_nodes.empty()) + { + auto it = free_nodes.begin(); + N_ID u = *it; + add_to_solution(u); + } +} + +void LocalSearch::improve(N_CONTAINER &IS) { + init(IS); + N_ID exit, enter1, enter2; + while (find_swap(exit, enter1, enter2)) + { + remove_from_solution(exit); + add_to_solution(enter1); + add_to_solution(enter2); + to_maximal(); + } + IS = deactivated_nodes; + return; +} \ No newline at end of file diff --git a/mwis/LocalSearch.h b/mwis/LocalSearch.h new file mode 100644 index 0000000..8b02e61 --- /dev/null +++ b/mwis/LocalSearch.h @@ -0,0 +1,61 @@ +// +// Created by margarita on 06/12/22. +// + +#ifndef QUANTUM_BNP_LOCALSEARCH_H +#define QUANTUM_BNP_LOCALSEARCH_H +#include "../Graph.h" + +/** + * This class allows to improve a solution for the independent set problem by performing local modifications. + * It implements the algorithm introduced in the paper [Fast Local Search for the Maximum Independent Set Problem] by D. Andrade, M. G. C. Resende and R. F. F. Werneck + */ +class LocalSearch { + const Graph* graph; + vector tightness; + N_CONTAINER active_nodes; + N_CONTAINER free_nodes; + N_CONTAINER deactivated_nodes; + + + /** Initialize the data structures required for a local search + * + * @param g + */ + void init(N_CONTAINER& IS); + + /** Find if there exists a 1-to-2 swap that improves the solution value + * + * @param exit stores the id of the node that should leave the solution + * @param enter1, enter2 store the id of the node that should enter the solution + * @return True if the method found an improving swap + */ + bool find_swap(N_ID& exit, N_ID & enter1, N_ID & enter2); + void remove_from_solution(const N_ID& u); + + /** Add the free node to the solution + * + * @param u + * @throw TODO + */ + void add_to_solution(const N_ID& u); + + /** Transform the stored independent set to the maximal one + * + * The method adds iteratively free nodes to the solution + */ + void to_maximal(); + +public: + + LocalSearch(const Graph *g) : graph(g) {}; + + /** Performs a local search from a better independent set around the initial point + * + * @param IS the initial solution obtained with a constructive heuristic + */ + void improve(N_CONTAINER& IS); +}; + + +#endif //QUANTUM_BNP_LOCALSEARCH_H diff --git a/mwis/cplex.cpp b/mwis/cplex.cpp new file mode 100644 index 0000000..ddd14b0 --- /dev/null +++ b/mwis/cplex.cpp @@ -0,0 +1,70 @@ +// +// Created by margarita on 10/12/22. +// +#ifdef QB_ENABLE_CPLEX +#include +#include "mwis.h" + +ILOSTLBEGIN + +bool cplexMWIS(const Graph& G, N_CONTAINER& best_mwis, WTYPE & best_mwis_value, const WTYPE & cutoff) +{ + auto active_in_graph = G.get_active_nodes(); + vector node_id(active_in_graph.begin(), active_in_graph.end()); + + IloEnv env; + IloModel model(env); + IloCplex cplex(model); + + IloBoolVarArray vars(env, active_in_graph.size()); + IloExpr obj_function(env); + + model.add(vars); + + for(int i = 0; i < node_id.size(); i++) { + + //add one constraint per edge to the model + for (int j = i + 1; j < node_id.size(); j++) + if (G.has_edge(node_id[i], node_id[j])) { + IloRange edge_cons(env, 0, 1); + edge_cons.setExpr(vars[i] + vars[j]); + //add constraint + model.add(edge_cons); + } + + //add variable to the objective function + obj_function += G.get_node_weight(node_id[i]) * vars[i]; + } + + IloObjective obj; + if(G.is_weighted()) + obj = IloMaximize(env, obj_function); + else + obj = IloMaximize(env, IloSum(vars)); + + model.add(obj); + + //Remove console logging + cplex.setOut(env.getNullStream()); + + cplex.solve(); + + //Recover the solution + N_CONTAINER cplex_IS; + WTYPE cplex_IS_weight = 0; + + for(int i = 0; i < node_id.size(); i++){ + auto val = cplex.getValue(vars[i]); + if(val > EPSILON){ + cplex_IS.insert(node_id[i]); + cplex_IS_weight += G.get_node_weight(node_id[i]); + } + } + if(cplex_IS_weight > best_mwis_value){ + best_mwis_value = cplex_IS_weight; + best_mwis = cplex_IS; + } + env.end(); + return cplex_IS_weight > cutoff; +} +#endif \ No newline at end of file diff --git a/mwis/greedy.cpp b/mwis/greedy.cpp new file mode 100644 index 0000000..ade1ead --- /dev/null +++ b/mwis/greedy.cpp @@ -0,0 +1,101 @@ +// +// Created by margarita on 09/12/22. +// +#include "mwis.h" +#include "LocalSearch.h" +#include +#include +#include + +//Number of different permutations of the order +#define N_ORDERS 5 + + +/** Find a Maximal Independent Set with respect to a given order + * + * @param graph + * @param priority the order of nodes + * @param dynamic true if the order is modified after a vertex is added to a solution + * @param best_curr_is stores the best known independent set + * @param best_curr_weight stores the weight of the best indepedent set + */ +void maximalIS(const Graph& graph, unordered_map& priority, bool dynamic, N_CONTAINER& best_curr_is, WTYPE& best_curr_weight) +{ + N_CONTAINER active_nodes = graph.get_active_nodes(); + N_CONTAINER IS; + + //Add active node with the highest priority + while (!active_nodes.empty()) + { + //Find node with the highest priority + auto it = max_element(active_nodes.begin(), active_nodes.end(), + [&priority](auto u, auto v) {return priority[u] < priority[v];}); + N_ID u = *it; + + //Eliminate the neighbors and modify priorities if necessary + for(const auto & v: graph.get_neighbors(u)) { + if(dynamic) + for(const auto & v_neighbor : graph.get_neighbors(v)){ + if(active_nodes.count(v_neighbor)) + priority[v_neighbor] += graph.get_node_weight(v_neighbor); + } + active_nodes.erase(v); + } + IS.insert(u); + active_nodes.erase(u); + } + + // Improve the greedy solution with local search + LocalSearch ls(&graph); + ls.improve(IS); + + //If the maximal independent set is better than the best previously known set - modify it + WTYPE maximal_is_weight = graph.get_nodeset_weight(IS); + if(maximal_is_weight > best_curr_weight){ + best_curr_is = IS; + best_curr_weight = maximal_is_weight; + } +} + + +bool greedyMWIS(const Graph& graph, N_CONTAINER& IS, WTYPE& IS_weight, const WTYPE& cutoff){ + unordered_map weight_priority; + for (const auto & u: graph.get_active_nodes()){ + weight_priority[u] = graph.get_node_weight(u); + } + + unordered_map surplus_priority = weight_priority; + for (const auto & u : graph.get_active_nodes()){ + for(const auto & v : graph.get_neighbors(u)) + surplus_priority[v] -= graph.get_node_weight(u); + } + + unordered_map dynamic_surplus_priority = surplus_priority; + + WTYPE factor = graph.get_node_number() * graph.get_max_weight(); + + //Iterate over different orders and first elements to get the best independent set + + for(int i = 0; i < N_ORDERS; i++){ + + //Find is maximal sets for any of orders improves the current best known independent set + maximalIS(graph, weight_priority, false, IS, IS_weight); + maximalIS(graph, surplus_priority, false, IS, IS_weight); + maximalIS(graph, dynamic_surplus_priority, true, IS, IS_weight); + + if(IS_weight > cutoff) break; + + //Move the top element to the end of the list + auto it_w = max_element(weight_priority.begin(), weight_priority.end(), [](auto u, auto v){ return u.first < v.first; }); + if(it_w!=weight_priority.end()) + it_w->second -= factor; + + + auto it_s = max_element(surplus_priority.begin(), surplus_priority.end(), [](auto u, auto v){ return u.first < v.first; }); + if(it_s!=weight_priority.end()) + it_s->second -= factor; + + dynamic_surplus_priority = surplus_priority; + } + return IS_weight > cutoff; +} \ No newline at end of file diff --git a/mwis/mwis.h b/mwis/mwis.h new file mode 100644 index 0000000..a87c3f1 --- /dev/null +++ b/mwis/mwis.h @@ -0,0 +1,65 @@ +// +// Created by margarita on 06/12/22. +// + +#ifndef QUANTUM_BNP_MWIS_H +#define QUANTUM_BNP_MWIS_H + +#include "../Graph.h" + + +/** A greedy heuristic that finds a weighted independent set of weight above some threshold + * + * It finds the maximal independent sets with respect to one of three orders and stops when the best_mwis > cutoff. + * If the required set is not found, orders are modified and the search continues for a fixed amount of steps. + * To get an approximately optimal weighted independent set we should set cutoff = INF. + * + * @param G the input graph + * @param best_mwis in input constains the best previously known MWIS, is modified if the function finds a better solution + * @param best_mwis_value the value of best_mwis + * @param cutoff + * @return True if the method finds an independent set of weight > cutoff + * @note The used orders are specified in the paper [Maximum-Weight Stable Sets and Safe Lower Bounds For Graph Coloring] + */ +bool greedyMWIS(const Graph& G, N_CONTAINER& best_mwis, WTYPE & best_mwis_value, const WTYPE & cutoff); + +/** A quantum heuristic based on RQAOA that finds a weighted independent set of weight above some threshold + * + * The method defines the Hamiltonian corresponding to the MWIS problem. Independence constraint is enforced with penalties. + * It uses RAOA to approximate ground states of the resulting Hamiltonian. + * If the approximate ground state correspond to an infeasible solution the set is modified to satisfy the constraints. + * + * @param G the input graph + * @param best_mwis in input constains the best previously known MWIS, is modified if the function finds a better solution + * @param best_mwis_value the value of best_mwis + * @param cutoff + * @return True if the method finds an independent set of weight > cutoff + * @note The used orders are specified in the paper [Maximum-Weight Stable Sets and Safe Lower Bounds For Graph Coloring] + */ +bool quantumMWIS(const Graph& G, N_CONTAINER& best_mwis, WTYPE & best_mwis_value, const WTYPE & cutoff); + +/** An exact method based on Branching that finds a weighted independent set of weight above some threshold + * + * The method stops when it find a set of weight < threshold. If threshold = INF the method finds an exact optimal solution + * + * @param G the input graph + * @param best_mwis in input constains the best previously known MWIS, is modified when the function finds a better solution + * @param best_mwis_value the value of best_mwis + * @param cutoff + * @return True if the method finds an independent set of weight > cutoff + * @note The method was introduced in the paper [Maximum-Weight Stable Sets and Safe Lower Bounds For Graph Coloring] + */ +//bool sewellMWIS(const Graph& G, N_CONTAINER& best_mwis, WTYPE & best_mwis_value, const WTYPE & cutoff); + +#ifdef QB_ENABLE_CPLEX +/** An exact method for MWIS solving the ILP formulation with CPLEX solver + * + * @param G the input graph + * @param best_mwis in input constains the best previously known MWIS, is modified when the function finds a better solution + * @param best_mwis_value the value of best_mwis + * @param cutoff + * @return True if the method finds an independent set of weight > cutoff + 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N{vRGAc?|#nK>$Tso5TPB literal 0 HcmV?d00001 diff --git a/quantum/Hamiltonian.cpp b/quantum/Hamiltonian.cpp new file mode 100644 index 0000000..11ea4ac --- /dev/null +++ b/quantum/Hamiltonian.cpp @@ -0,0 +1,396 @@ +// +// Created by margarita on 06/12/22. +// + +#include "Hamiltonian.h" +#include "../mwis/LocalSearch.h" +#include "nlopt.hpp" +#include +#include +#include +#include +#include + +// Time budget for global parameter optimization routine + +#define MAX_OPT_TIME 10 + +void Hamiltonian::update_common_neighbors() { + for(const auto& u: active_nodes) + for(const auto& v: active_nodes) + if(u < v) { + common_neighbors[u][v] = neighbors[u]; + common_neighbors[u][v].insert(neighbors[v].begin(), neighbors[v].end()); + common_neighbors[u][v].erase(u); + common_neighbors[u][v].erase(v); + common_neighbors[v][u] = common_neighbors[u][v]; + } + return; +} + +void Hamiltonian::set_linear(const N_ID &u, CTYPE weight) { + if(active_nodes.count(u)) linear[u] = weight; +} + +void Hamiltonian::set_quadratic(const N_ID &u, const N_ID &v, CTYPE weight) { + if(abs(weight) < EPSILON) + { + neighbors[u].erase(v); + neighbors[v].erase(u); + } + else + { + neighbors[u].insert(v); + neighbors[v].insert(u); + } + quadratic[u*allocated + v] = quadratic[v*allocated + u] = weight; +} + +double Hamiltonian::z_mean(const N_ID &u, const Parameters &p) const { + if (abs(linear[u]) < EPSILON) return 0; + double zu = sin(p.beta) * sin(p.gamma * linear[u]); + for(const auto & v: neighbors[u]) + zu *= cos(p.gamma * quadratic[u*allocated + v]); + return zu; +} + +double Hamiltonian::zz_mean(const N_ID &u, const N_ID &v, const Parameters &p) const { + double zuv = 0; + if( abs(quadratic[u*allocated + v]) > EPSILON) + { + double cu = cos(p.gamma * linear[u]); + for(const auto & x : neighbors[u]) + if(x != v) + cu *= cos(p.gamma * quadratic[u*allocated + x]); + double cv = cos(p.gamma * linear[v]); + for(const auto & x: neighbors[v]) + if(x != u) + cv *= cos(p.gamma * quadratic[v*allocated + x]); + zuv = sin(2*p.beta)*sin(p.gamma * quadratic[u*allocated + v])*(cu + cv); + } + double cplus = cos(p.gamma * (linear[u] + linear[v])); + double cminus = cos(p.gamma * (linear[u] - linear[v])); + for(const auto & x: common_neighbors[u][v]) + { + cplus *= cos(p.gamma * (quadratic[u*allocated + x] + quadratic[v*allocated + x])); + cminus *= cos(p.gamma * (quadratic[u*allocated + x] - quadratic[v*allocated + x])); + } + zuv += (sin(p.beta) * sin(p.beta))*(cminus - cplus); + return zuv/2; +} + +double Hamiltonian::qaoa_mean(const Parameters &p) const { + double mean = 0; + for(auto it1 = active_nodes.begin(); it1 != active_nodes.end(); it1++) { + + if(!abs(linear[*it1]) < EPSILON) + mean += linear[*it1] * z_mean(*it1, p); + for(auto it2 = next(it1); it2 != active_nodes.end(); it2++) + if(!abs(quadratic[*it1*allocated + *it2]) < EPSILON) + mean += quadratic[*it1*allocated + *it2] * zz_mean(*it1, *it2, p); + } + return mean; +} + +void Hamiltonian::remove_node(const N_ID &u) { + for (const auto &v: neighbors[u]) + neighbors[v].erase(u); + + active_nodes.erase(u); + actual_node_number--; +} + +void Hamiltonian::add_constraint(Constraint c) { + constraints.push_back(c); + if(c.v != -1) + linear[c.v] += c.sigma * linear[c.u]; + for(const auto& w: neighbors[c.u]) + if(w != c.v) { + if (c.v != -1) + set_quadratic(c.v, w, quadratic[c.v * allocated + w] + c.sigma * quadratic[c.u * allocated + w]); + else + set_linear(w, linear[w] + c.sigma * quadratic[c.u * allocated + w]); + } + remove_node(c.u); + return; +} + + + +void Hamiltonian::optimize_parameters(Parameters& p, bool& in_neighborhood) const { + + // Compute how much time takes the optimization + + auto start = std::chrono::system_clock::now(); + + //The objective function + auto f = [](const vector &x, vector&, void* f_data){ + auto instance = (Hamiltonian* ) f_data; + return instance->qaoa_mean({x[0], x[1]}); + }; + + //The parameter vector + vector opt_x(2); + + //The optimum value + double opt_val; + + // Set up the optimizer + nlopt::opt local_optimizer(nlopt::algorithm::LN_BOBYQA, 2); + + //Termination condition + local_optimizer.set_xtol_abs(0.0001); + local_optimizer.set_ftol_rel(0.01); + + //If the initial point is not specified find it with a global search + + if(!in_neighborhood) { + //Optimization routines + nlopt::opt global_optimizer(nlopt::algorithm::GD_MLSL, 2); + global_optimizer.set_local_optimizer(local_optimizer); + + //Set the objective + global_optimizer.set_min_objective(f, (void *) this); + + //Bounds + global_optimizer.set_population(actual_node_number); + global_optimizer.set_lower_bounds(0); + + //Termination condition + global_optimizer.set_upper_bounds(2* M_PI); + global_optimizer.set_xtol_abs(0.001); + global_optimizer.set_maxtime(MAX_OPT_TIME); + + global_optimizer.optimize(opt_x, opt_val); + } + else + { + opt_x[0] = p.beta; + opt_x[1] = p.gamma; + } + + //Search around the initialization point with a local method + + //Set bounds + local_optimizer.set_lower_bounds(0); + local_optimizer.set_upper_bounds(2* M_PI); + + //Strengthen the termination condition + local_optimizer.set_ftol_rel(0.001); + local_optimizer.set_maxtime(MAX_OPT_TIME); + + local_optimizer.set_min_objective(f, (void *) this); + local_optimizer.optimize(opt_x, opt_val); + + auto elapsed_seconds = std::chrono::system_clock::now()-start; + p.beta = opt_x[0]; + p.gamma = opt_x[1]; + in_neighborhood = true; +// cout << "Optimal parameters: " << opt_x[0] << " " << opt_x[1] << endl; +} + +Constraint Hamiltonian::find_max_correlation(const Parameters &p) { + Constraint output = {1, *active_nodes.begin(), -1}; + double max_abs_corr_value = 0; + for(auto const & u: active_nodes) + { + double val = z_mean(u, p); + if ( abs(val) > max_abs_corr_value) + { + max_abs_corr_value = abs(val); + int sigma = val < 0 ? -1 : 1; + output = {sigma, u, -1}; + } + for(auto const &v : active_nodes) + if(u < v) + { + double val = zz_mean(u, v, p); + if (abs(val) > max_abs_corr_value) + { + max_abs_corr_value = abs(val); + int sigma = val < 0 ? -1 : 1; + output = {sigma, u, v}; + } + } + } +// cout << "Maximum correlation: " << max_abs_corr_value << "; "; + return output; +} + +bool next_vector(vector& proper_vector) +{ + for (int i = proper_vector.size()-1; i >=0; i--) + if(proper_vector[i]==-1) + { + proper_vector[i] = 1; + return true; + } + else + proper_vector[i] = -1; + return false; +}; + +void Hamiltonian::solve_by_brute_force() { + + vector best_vector(actual_node_number, -1); + vector proper_vector = best_vector; + + vector node_id(active_nodes.begin(), active_nodes.end()); + + // TODO throw an exception if the size is too large + CTYPE min_val = INT_MAX; + do + { + CTYPE value = 0; + for(int i = 0; i < actual_node_number; i++) { + value += linear[node_id[i]] * proper_vector[i]; + for(int j = i+1; j < actual_node_number; j++) + value += quadratic[node_id[i] * allocated + node_id[j]] * proper_vector[i] * proper_vector[j]; + } + if(value < min_val) { + min_val = value; + best_vector = proper_vector; + } + } + while(next_vector(proper_vector)); + + for(int i = 0; i < actual_node_number; i++) + constraints.push_back({best_vector[i], node_id[i], -1}); + active_nodes.clear(); + return; +} + + +vector Hamiltonian::rqaoa() { + bool params_are_initialized = false; + Parameters p; + + //Eliminate nodes until the problem becomes sufficiently small for the brute-force method + while (actual_node_number > BF_LIMIT){ + update_common_neighbors(); + optimize_parameters(p, params_are_initialized); + Constraint c = find_max_correlation(p); + // cout << c.sigma << " " << c.v << " " << c.u; + add_constraint(c); + } + //Solve the small problem with brute-force groundstate search + solve_by_brute_force(); + + vector result(allocated, -1); + while(!constraints.empty()) + { + Constraint c = constraints.back(); + c.v == -1 ? result[c.u] = c.sigma : result[c.u] = c.sigma * result[c.v]; + constraints.pop_back(); + } + return result; +} + +/**Initialize the instance of Hamiltonian whose ground state encodes the Maximum Weighted Independent Set + * + * @param graph + * @param node_id stores the association between variables in hamiltonian and nodes in the graph + * @return + */ +Hamiltonian get_MWIS_Hamiltonian(const Graph& graph, vector& node_id) +{ + //Recover active nodes + N_CONTAINER active_in_graph = graph.get_active_nodes(); + + //Remove the nodes of zero weight from consideration + auto it = active_in_graph.begin(); + while(it != active_in_graph.end()) + { + if (abs(graph.get_node_weight(*it)) < EPSILON) + it = active_in_graph.erase(it); + else + it++; + } + + int n_vars = active_in_graph.size(); // Number of variables in the Hamiltonian + + //Associate to each active node of non-zero weight a variable index in the Hamiltonian + + node_id = vector(active_in_graph.begin(), active_in_graph.end()); + Hamiltonian h(n_vars); + + //Penalty + WTYPE max_weight = graph.get_max_weight(); + CTYPE lambda = 1 + ceil(max_weight); + + //Transform double weights to integer ones for weighted graphs to ensure period [0, 2pi] in parameter values + int scale = 1; + + if(graph.is_weighted()) + scale = n_vars / max_weight; + + lambda *= scale; + + vector integer_weights; + for(const auto& u: active_in_graph) { + //Minus sign as we transform maximization to minimization + WTYPE scaled_coeff = -round(2 * scale * graph.get_node_weight(u)); + for(const auto& v: active_in_graph){ + if(graph.has_edge(u, v)) + scaled_coeff += lambda; + } + integer_weights.push_back(scaled_coeff); + } + + //Divide all coefficients by the greatest common divisor to reinsure that the period is not a subspace of [0, 2pi] + int divisor = lambda; + for(const auto& coeff: integer_weights) + divisor = gcd(divisor, coeff); + for(auto& coeff : integer_weights) + coeff /= divisor; + lambda /= divisor; + + //Initialize the Hamiltonian + for(int i = 0; i < n_vars; i++) + h.set_linear(i, integer_weights[i]); + + for(int i = 0; i < n_vars; i++) + for(int j = i+1; j < n_vars; j++) + { + if (graph.has_edge(node_id[i], node_id[j])) + h.set_quadratic(i, j, lambda); + } + + return h; +} + + +bool quantumMWIS(const Graph& graph, N_CONTAINER& IS, WTYPE& IS_weight, const WTYPE& cutoff) +{ + //Initialize the problem + vector node_id; + Hamiltonian h = get_MWIS_Hamiltonian(graph, node_id); + + //Find the ground state + auto approx_ground_state = h.rqaoa(); + + //Recover the solution + N_CONTAINER rqaoa_is; + for(int i = 0; i < node_id.size(); i++) + if(approx_ground_state[i] == 1) + rqaoa_is.insert(node_id[i]); + + if(! is_independent_set(graph, rqaoa_is)){ + cout << "RQAOA OBTAINED UNFEASIBLE SOLUTION." << endl; + return false; + } + +//Improve the solution found by RQAOA with local search + LocalSearch ls(&graph); + ls.improve(rqaoa_is); + + WTYPE rqaoa_weight = 0; + for (const auto& u: rqaoa_is) + rqaoa_weight += graph.get_node_weight(u); + + if(rqaoa_weight > IS_weight){ + IS_weight = rqaoa_weight; + IS = rqaoa_is; + } + return IS_weight > cutoff; +} diff --git a/quantum/Hamiltonian.h b/quantum/Hamiltonian.h new file mode 100644 index 0000000..643478b --- /dev/null +++ b/quantum/Hamiltonian.h @@ -0,0 +1,160 @@ +// +// Created by margarita on 06/12/22. +// + +#ifndef QUANTUM_BNP_HAMILTONIAN_H +#define QUANTUM_BNP_HAMILTONIAN_H + +#include "../Graph.h" +#include "../mwis/mwis.h" +#include + +// Threshold for the brute-force solution + +#define BF_LIMIT 12 + +using CTYPE = int; + +using Parameters = struct Parameters +{ + double beta; + double gamma; +}; + + +/** A quantum heuristic based on RQAOA that finds a weighted independent set of weight above some threshold + * + * The method defines the Hamiltonian corresponding to the MWIS problem. Independence constraint is enforced with penalties. + * It uses RAOA to approximate ground states of the resulting Hamiltonian. + * If the approximate ground state correspond to an infeasible solution the set is modified to satisfy the constraints. + * + * @param G the input graph + * @param best_mwis in input constains the best previously known MWIS, is modified if the function finds a better solution + * @param best_mwis_value the value of best_mwis + * @param cutoff + * @return True if the method finds an independent set of weight > cutoff + * @note The used orders are specified in the paper [Maximum-Weight Stable Sets and Safe Lower Bounds For Graph Coloring] + */ +bool quantumMWIS(const Graph& G, N_CONTAINER& best_mwis, WTYPE & best_mwis_value, const WTYPE & cutoff); + +using Constraint = struct Constraint{ + //The value -1 or +1 that should take the variable Z_u (or the pair Z_u Z_v) + int sigma; + + //The first node in the constraint + N_ID u; + + //The second node in the constraint, if v = -1 than the constraint involves only the node u (Z_u = sigma), otherwise Z_uZ_v = sigma + N_ID v; +}; + +class Hamiltonian { + + //Inital size of the instance (before RQAOA) + int allocated; + + //Size of the instance at the current step of RQAOA + int actual_node_number; + + //Nodes not eliminated at the current step of RQAOA + N_CONTAINER active_nodes; + + //Constraints added by RQAOA + list constraints; + + //For each active node stores a list of other nodes connected by a non-zero interaction term J_i,j in the Ising Hamiltonian + vector neighbors; + + //Service structure - for each pair of active nodes stores the union of their neighbors, accelerate the computation of mean values. + vector> common_neighbors; + + //Linear coefficients of the Ising model + vector linear; + + //Quadratic coefficients of the Ising model + vector quadratic; + + /** After a variable is removed and the instance is modified - updates the list of common neighbors + * + */ + void update_common_neighbors(); + +public: + Hamiltonian(int n): linear(n, 0), quadratic(n*n, 0), actual_node_number(n), allocated(n), neighbors(n), common_neighbors(n, vector(n)) { + for(int i = 0; i < n; i++) + active_nodes.insert(i); + }; + + /** Compute the mean value of the operator Z_u + * + * @param u id of the node + * @param p parameters of QAOA_1 circuit + * @return the mean value + */ + double z_mean(const N_ID& u, const Parameters& p) const; + /** Compute the mean value of the operator Z_u,v + * + * @param u id of the node + * @param p parameters of QAOA_1 circuit + * @return the mean value + */ + double zz_mean(const N_ID& u, const N_ID& v, const Parameters& p) const; + + /** Compute the mean energy of the Hamiltonian at the point p the with an analytical function + * + * @param p + * @return the mean energy in QAOA_1(p.beta, p.gamma) state + */ + double qaoa_mean(const Parameters& p) const; + + /** Modifies the linear coefficient of the node u + * + * @param u + * @param weight + */ + void set_linear(const N_ID& u, CTYPE weight); + + /** Modifies the quadratic coefficient of the term Z_uZ_v + * + * @param u + * @param v + * @param weight + */ + void set_quadratic(const N_ID& u, const N_ID& v, CTYPE weight); + + + void remove_node(const N_ID& u); + + /** Add a constraint, modify the Hamiltonian, and remove a variable + * + * @param c + */ + void add_constraint(Constraint c); + + /** Optimize parameters of QAOA for the Hamiltonian + * + * @param p + * @param in_neighborhood True if we search for an optimum in the neighborhood of p + * @throw TODO an exception when the optimizer fails (see nlopt::opt::optimize) + * @note If the initial point is not provided finds it with a multistart global search. Then use BOBYQA method for the local search + */ + void optimize_parameters(Parameters& p, bool& in_neighborhood) const; + + Constraint find_max_correlation(const Parameters& p); + + /** Compute the exact ground state of the Hamiltonian with a brute-force approach + * + * If the number of active nodes is larger than BF_limit throw an exception + * @throw TODO if the instance is too large + */ + void solve_by_brute_force(); + + /** Compute the approximate ground state of the Hamiltonian with RQAOA + * + * @return an approximate solution x \in {-1, 1}^n + * @note the algorithm was introduced in the paper [Obstacles to State Preparation and Variational Optimization from Symmetry Protection] by S/ Bravyi, A. Kliesch, R. Koenig, E. Tang + */ + vector rqaoa(); +}; + +#endif //QUANTUM_BNP_HAMILTONIAN_H diff --git a/test_data/graphs_100/Complete.mwis b/test_data/graphs_100/Complete.mwis new file mode 100644 index 0000000..dd1242b --- /dev/null +++ b/test_data/graphs_100/Complete.mwis @@ -0,0 +1,5052 @@ +c m [0] +p edge 100 4950 +e 1 2 +e 1 3 +e 1 4 +e 1 5 +e 1 6 +e 1 7 +e 1 8 +e 1 9 +e 1 10 +e 1 11 +e 1 12 +e 1 13 +e 1 14 +e 1 15 +e 1 16 +e 1 17 +e 1 18 +e 1 19 +e 1 20 +e 1 21 +e 1 22 +e 1 23 +e 1 24 +e 1 25 +e 1 26 +e 1 27 +e 1 28 +e 1 29 +e 1 30 +e 1 31 +e 1 32 +e 1 33 +e 1 34 +e 1 35 +e 1 36 +e 1 37 +e 1 38 +e 1 39 +e 1 40 +e 1 41 +e 1 42 +e 1 43 +e 1 44 +e 1 45 +e 1 46 +e 1 47 +e 1 48 +e 1 49 +e 1 50 +e 1 51 +e 1 52 +e 1 53 +e 1 54 +e 1 55 +e 1 56 +e 1 57 +e 1 58 +e 1 59 +e 1 60 +e 1 61 +e 1 62 +e 1 63 +e 1 64 +e 1 65 +e 1 66 +e 1 67 +e 1 68 +e 1 69 +e 1 70 +e 1 71 +e 1 72 +e 1 73 +e 1 74 +e 1 75 +e 1 76 +e 1 77 +e 1 78 +e 1 79 +e 1 80 +e 1 81 +e 1 82 +e 1 83 +e 1 84 +e 1 85 +e 1 86 +e 1 87 +e 1 88 +e 1 89 +e 1 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+c m [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 52, 53, 55, 57, 59, 61, 64, 65, 66, 70, 71, 72, 78, 79, 80, 81, 82, 83, 84, 92, 93, 94, 95, 96, 97, 98, 99, 100] +p edge 100 99 +e 1 2 +e 2 3 +e 3 4 +e 4 5 +e 5 6 +e 6 7 +e 7 8 +e 8 9 +e 9 10 +e 10 11 +e 11 12 +e 12 13 +e 13 14 +e 14 15 +e 15 16 +e 16 17 +e 17 18 +e 18 19 +e 19 20 +e 20 21 +e 21 22 +e 22 23 +e 23 24 +e 24 25 +e 25 26 +e 26 27 +e 27 28 +e 28 29 +e 29 30 +e 30 31 +e 31 32 +e 32 33 +e 33 34 +e 34 35 +e 35 36 +e 35 53 +e 36 37 +e 36 54 +e 37 38 +e 37 55 +e 38 39 +e 38 56 +e 39 40 +e 39 57 +e 40 41 +e 40 58 +e 41 42 +e 41 59 +e 42 43 +e 42 60 +e 43 44 +e 43 61 +e 44 45 +e 44 62 +e 44 63 +e 45 46 +e 45 64 +e 45 65 +e 45 66 +e 46 47 +e 46 67 +e 46 68 +e 46 69 +e 47 48 +e 47 70 +e 47 71 +e 47 72 +e 48 49 +e 48 73 +e 48 74 +e 48 75 +e 48 76 +e 48 77 +e 49 50 +e 49 78 +e 49 79 +e 49 80 +e 49 81 +e 49 82 +e 49 83 +e 49 84 +e 50 51 +e 50 85 +e 50 86 +e 50 87 +e 50 88 +e 50 89 +e 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100644 index 0000000..8a71aa5 --- /dev/null +++ b/test_data/graphs_20/Complete.mwis @@ -0,0 +1,212 @@ +c m [0] +p edge 20 190 +e 1 2 +e 1 3 +e 1 4 +e 1 5 +e 1 6 +e 1 7 +e 1 8 +e 1 9 +e 1 10 +e 1 11 +e 1 12 +e 1 13 +e 1 14 +e 1 15 +e 1 16 +e 1 17 +e 1 18 +e 1 19 +e 1 20 +e 2 3 +e 2 4 +e 2 5 +e 2 6 +e 2 7 +e 2 8 +e 2 9 +e 2 10 +e 2 11 +e 2 12 +e 2 13 +e 2 14 +e 2 15 +e 2 16 +e 2 17 +e 2 18 +e 2 19 +e 2 20 +e 3 4 +e 3 5 +e 3 6 +e 3 7 +e 3 8 +e 3 9 +e 3 10 +e 3 11 +e 3 12 +e 3 13 +e 3 14 +e 3 15 +e 3 16 +e 3 17 +e 3 18 +e 3 19 +e 3 20 +e 4 5 +e 4 6 +e 4 7 +e 4 8 +e 4 9 +e 4 10 +e 4 11 +e 4 12 +e 4 13 +e 4 14 +e 4 15 +e 4 16 +e 4 17 +e 4 18 +e 4 19 +e 4 20 +e 5 6 +e 5 7 +e 5 8 +e 5 9 +e 5 10 +e 5 11 +e 5 12 +e 5 13 +e 5 14 +e 5 15 +e 5 16 +e 5 17 +e 5 18 +e 5 19 +e 5 20 +e 6 7 +e 6 8 +e 6 9 +e 6 10 +e 6 11 +e 6 12 +e 6 13 +e 6 14 +e 6 15 +e 6 16 +e 6 17 +e 6 18 +e 6 19 +e 6 20 +e 7 8 +e 7 9 +e 7 10 +e 7 11 +e 7 12 +e 7 13 +e 7 14 +e 7 15 +e 7 16 +e 7 17 +e 7 18 +e 7 19 +e 7 20 +e 8 9 +e 8 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1 8 +e 1 9 +e 1 10 +e 1 11 +e 1 12 +e 1 13 +e 1 14 +e 1 15 +e 1 16 +e 1 17 +e 1 18 +e 1 19 +e 1 20 +e 1 21 +n 1 1 +n 2 1 +n 3 1 +n 4 1 +n 5 1 +n 6 1 +n 7 1 +n 8 1 +n 9 1 +n 10 1 +n 11 1 +n 12 1 +n 13 1 +n 14 1 +n 15 1 +n 16 1 +n 17 1 +n 18 1 +n 19 1 +n 20 1 +n 21 1 diff --git a/test_data/graphs_20/Tree.mwis b/test_data/graphs_20/Tree.mwis new file mode 100644 index 0000000..1782dd2 --- /dev/null +++ b/test_data/graphs_20/Tree.mwis @@ -0,0 +1,41 @@ +c m [2, 4, 6, 8, 10, 12, 17, 18, 19, 20] +p edge 20 19 +e 1 2 +e 2 3 +e 3 4 +e 4 5 +e 5 6 +e 6 7 +e 6 11 +e 7 8 +e 7 12 +e 8 9 +e 8 13 +e 8 14 +e 8 15 +e 8 16 +e 9 10 +e 9 17 +e 9 18 +e 9 19 +e 9 20 +n 1 1 +n 2 1 +n 3 1 +n 4 1 +n 5 1 +n 6 1 +n 7 1 +n 8 1 +n 9 1 +n 10 1 +n 11 1 +n 12 1 +n 13 1 +n 14 1 +n 15 1 +n 16 1 +n 17 1 +n 18 1 +n 19 1 +n 20 1 diff --git a/test_data/graphs_40/GNP_0.1.mwis b/test_data/graphs_40/GNP_0.1.mwis new file mode 100644 index 0000000..ee8609f --- /dev/null +++ b/test_data/graphs_40/GNP_0.1.mwis @@ -0,0 +1,122 @@ 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38 1 +n 39 1 +n 40 1 diff --git a/test_data/graphs_40/GNP_0.2.mwis b/test_data/graphs_40/GNP_0.2.mwis new file mode 100644 index 0000000..28a9e51 --- /dev/null +++ b/test_data/graphs_40/GNP_0.2.mwis @@ -0,0 +1,213 @@ +p edge 40 172 +e 1 7 +e 1 11 +e 1 29 +e 1 33 +e 1 35 +e 1 39 +e 1 40 +e 2 4 +e 2 8 +e 2 15 +e 2 16 +e 2 19 +e 2 20 +e 2 21 +e 2 25 +e 2 26 +e 2 33 +e 2 40 +e 3 11 +e 3 12 +e 3 13 +e 3 16 +e 3 17 +e 3 21 +e 3 22 +e 3 23 +e 3 27 +e 4 5 +e 4 6 +e 4 10 +e 4 12 +e 4 13 +e 4 24 +e 4 26 +e 4 30 +e 5 6 +e 5 7 +e 5 9 +e 5 11 +e 5 21 +e 5 23 +e 5 24 +e 5 35 +e 6 7 +e 6 11 +e 6 12 +e 6 17 +e 6 20 +e 6 21 +e 6 22 +e 6 23 +e 6 26 +e 6 28 +e 6 31 +e 6 39 +e 7 9 +e 7 13 +e 7 18 +e 7 20 +e 7 21 +e 7 23 +e 7 29 +e 7 36 +e 7 37 +e 8 11 +e 8 22 +e 8 29 +e 8 30 +e 8 34 +e 8 40 +e 9 11 +e 9 20 +e 9 21 +e 9 29 +e 9 31 +e 9 33 +e 9 35 +e 9 37 +e 10 19 +e 10 22 +e 10 24 +e 10 29 +e 10 31 +e 11 13 +e 11 15 +e 11 20 +e 11 22 +e 11 26 +e 11 30 +e 11 31 +e 11 36 +e 11 39 +e 12 19 +e 12 24 +e 12 26 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